Model Pulse
Collection
Daily download and like history for every model, dataset and Space on the Hub, plus Paper Pulse. Article: hf.co/blog/tardellirs/model-pulse • 4 items • Updated
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classes | week large_stringclasses 179
values | month large_stringdate 2023-05-01 00:00:00 2026-10-01 00:00:00 | early bool 2
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classes |
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2308.01320 | 2023-08-04 | DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales | [
"Zhewei Yao",
"Reza Yazdani Aminabadi",
"Olatunji Ruwase",
"Samyam Rajbhandari",
"Xiaoxia Wu",
"Ammar Ahmad Awan",
"Jeff Rasley",
"Minjia Zhang",
"Conglong Li",
"Connor Holmes",
"Zhongzhu Zhou",
"Michael Wyatt",
"Molly Smith",
"Lev Kurilenko",
"Heyang Qin",
"Masahiro Tanaka",
"Shuai ... | https://github.com/microsoft/DeepSpeed | null | 46 | 3 | 46 | 2024-03-12 | null | null | null | null | 1 | 46 | true | 2023-W31 | 2023-08 | true | 1 | 12 | 2 | 42 | 3 | 114 | ChatGPT-like models have revolutionized various applications in artificial
intelligence, from summarization and coding to translation, matching or even
surpassing human performance. However, the current landscape lacks an
accessible, efficient, and cost-effective end-to-end RLHF (Reinforcement
Learning with Human Feedb... | [
{
"name": "Zhewei Yao",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Reza Yazdani Aminabadi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Olatunji Ruwase",
... | null | null | null | akhaliq | AK | 43,183 | 2023-08-02T18:49:57.000Z | true | ||
2411.01747 | 2024-11-05 | DynaSaur: Large Language Agents Beyond Predefined Actions | [
"Dang Nguyen",
"Viet Dac Lai",
"Seunghyun Yoon",
"Ryan A. Rossi",
"Handong Zhao",
"Ruiyi Zhang",
"Puneet Mathur",
"Nedim Lipka",
"Yu Wang",
"Trung Bui",
"Franck Dernoncourt",
"Tianyi Zhou"
] | https://github.com/adobe-research/dynasaur | null | 38 | 3 | 38 | 2024-11-05 | 10 | 13 | 13 | 13 | 1 | 13 | true | 2024-W45 | 2024-11 | false | 13 | 23 | 41 | 76 | 139 | 285 | Existing LLM agent systems typically select actions from a fixed and
predefined set at every step. While this approach is effective in closed,
narrowly-scoped environments, we argue that it presents two major challenges
when deploying LLM agents in real-world scenarios: (1) selecting from a fixed
set of actions signifi... | [
{
"name": "Dang Nguyen",
"user": "dangmn",
"fullname": "Dang Nguyen",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64ba4c2565535cf237da429a/y_9RrS3V7FZutZV4f38nY.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Viet Dac Lai",
"user": "laivi... | null | null | null | Franck-Dernoncourt | Franck Dernoncourt | /avatars/5a151713b9eae8dc566f5957acee3475.svg | 360 | 2024-11-04T02:08:59.000Z | false | |
2407.11793 | 2024-07-17 | Click-Gaussian: Interactive Segmentation to Any 3D Gaussians | [
"Seokhun Choi",
"Hyeonseop Song",
"Jaechul Kim",
"Taehyeong Kim",
"Hoseok Do"
] | null | null | 3 | 3 | 3 | 2024-07-17 | 2 | 3 | 3 | 3 | 0 | 3 | true | 2024-W29 | 2024-07 | false | 18 | 19 | 78 | 86 | 320 | 345 | Interactive segmentation of 3D Gaussians opens a great opportunity for
real-time manipulation of 3D scenes thanks to the real-time rendering
capability of 3D Gaussian Splatting. However, the current methods suffer from
time-consuming post-processing to deal with noisy segmentation output. Also,
they struggle to provide... | [
{
"name": "Seokhun Choi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Hyeonseop Song",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jaechul Kim",
"user":... | null | null | null | akhaliq | AK | null | 2024-07-16T14:49:27.000Z | false | ||
2609.32540 | 2026-09-29 | In-Flight KV Cache with Clean Anchors for Faster Autoregressive Video Diffusion | [
"Yikai Wang",
"Xiao Han",
"Mengmeng Xu",
"Juan Camilo Perez",
"Yiannis Douratsos",
"Sen He",
"Zijian Zhou",
"Fei Zhang",
"Zhaochong An",
"Juan-Manuel Perez-Rua",
"Chen Change Loy",
"Tao Xiang"
] | null | https://yikai-wang.github.io/FlashForward/ | 35 | 2 | 35 | 2026-09-29 | 20 | 23 | 33 | 35 | 0 | 35 | true | 2026-W40 | 2026-09 | false | 22 | 109 | 118 | 404 | 222 | 786 | Few-step autoregressive video diffusion generates a long video by splitting the video into temporal chunks and generating chunk-by-chunk, each through a short sequence of denoising stages. To memorize chunks that are already generated, previous methods reconstruct a clean or less-noisy key--value (KV) cache by addition... | [
{
"name": "Yikai Wang",
"user": "yikaiwang",
"fullname": "Yikai Wang",
"avatar": "/avatars/6e5350fd998f0a7a4143d7504218164a.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Xiao Han",
"user": "BBrandonHanX",
"fullname": "Brandon Han",
"avatar": "https://c... | meta | Meta | yikaiwang | Yikai Wang | /avatars/6e5350fd998f0a7a4143d7504218164a.svg | null | 2026-09-26T00:00:00.000Z | true | ||
2412.06781 | 2024-12-10 | Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation | [
"Nicolas Dufour",
"David Picard",
"Vicky Kalogeiton",
"Loic Landrieu"
] | https://github.com/nicolas-dufour/plonk | null | 23 | 2 | 24 | 2024-12-10 | 9 | 14 | 16 | 18 | 1 | 18 | true | 2024-W50 | 2024-12 | false | 6 | 17 | 34 | 102 | 130 | 392 | Global visual geolocation predicts where an image was captured on Earth.
Since images vary in how precisely they can be localized, this task inherently
involves a significant degree of ambiguity. However, existing approaches are
deterministic and overlook this aspect. In this paper, we aim to close the gap
between trad... | [
{
"name": "Nicolas Dufour",
"user": "nicolas-dufour",
"fullname": "Nicolas Dufour",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/630652803aed65d34e98eee3/XG_PuVFA6ziGQZd3UUZSF.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "David Picard",
... | null | null | null | nicolas-dufour | Nicolas Dufour | 304 | 2024-12-09T18:59:04.000Z | true | ||
2603.01655 | 2026-03-04 | Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modeling | [
"Jérome Eertmans",
"Enrico M. Vitucci",
"Vittorio Degli-Esposti",
"Nicola Di Cicco",
"Laurent Jacques",
"Claude Oestges"
] | https://github.com/jeertmans/sampling-paths | https://differt.rtfd.io/npjwt2026/notebooks/sampling-paths.html | 0 | 4 | 0 | 2026-03-04 | 0 | 0 | 0 | 0 | 0 | 0 | true | 2026-W10 | 2026-03 | false | 42 | 43 | 147 | 151 | 720 | 745 | Ray tracing has become a standard for accurate radio propagation modeling, but suffers from exponential computational complexity, as the number of candidate paths scales with the number of objects raised to the power of the interaction order. This bottleneck limits its use in large-scale or real-time applications, forc... | [
{
"name": "Jérome Eertmans",
"user": "jeertmans",
"fullname": "Jérome Eertmans",
"avatar": "/avatars/46b0fdedd4bfe24a3ea4fa939c9b5bc3.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Enrico M. Vitucci",
"user": null,
"fullname": null,
"avatar": null,
... | UCLouvain | Université Catholique de Louvain | jeertmans | Jérome Eertmans | /avatars/46b0fdedd4bfe24a3ea4fa939c9b5bc3.svg | 7 | 2026-03-02T09:37:34.000Z | true | ||
2610.00313 | 2026-10-02 | Rules to Tools: Executable Checks for LLM Agents in Scientific Computing | [
"Jingjie Ning",
"Guojiang Zhao",
"Chen Xu",
"Shanshan Zhong",
"Xiaochuan Li",
"Ji Zeng",
"Guolin Ke"
] | null | null | 11 | 2 | 11 | 2026-10-02 | 4 | 8 | 10 | 11 | 0 | 11 | true | 2026-W40 | 2026-10 | false | 64 | 84 | 228 | 404 | 648 | 1,077 | Scientific coding agents receive equations, boundary conditions, and output requirements in writing, then must assess the programs they revise. Rules to Tools (R2T) supplies prepared executable checks of public scientific requirements. Matched SciCode repair groups share written checks, starting programs, model, and bu... | [
{
"name": "Jingjie Ning",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Guojiang Zhao",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Chen Xu",
"user": null... | AbhiVakil29112001 | Carnegie Mellon University | ethanning | Ethan Ning | null | 2026-09-29T00:00:00.000Z | false | |||
2603.13715 | 2026-03-18 | Measuring Primitive Accumulation: An Information-Theoretic Approach to Capitalist Enclosure in PIK2, Indonesia | [
"Sandy Hardian Susanto Herho",
"Alfita Puspa Handayani",
"Karina Aprilia Sujatmiko",
"Faruq Khadami",
"Iwan Pramesti Anwar"
] | https://github.com/sandyherho/supplPIK2LULC | null | 0 | 2 | 0 | 2026-03-18 | 0 | 0 | 0 | 0 | 0 | 0 | true | 2026-W12 | 2026-03 | false | 50 | 52 | 186 | 194 | 720 | 745 | Large-scale land enclosure for speculative mega-development constitutes a non-equilibrium spatial process whose velocity, topology, and irreversibility remain poorly quantified. We study the Pantai Indah Kapuk 2 (PIK2) coastal mega-development north of Jakarta, Indonesia, using eight years (2017--2024) of Sentinel-2 la... | [
{
"name": "Sandy Hardian Susanto Herho",
"user": "sandyherho",
"fullname": "Sandy Hardian Susanto Herho",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/68d51061ab9204b0c8a0ceb2/CVmg6wo4yBqIZgGZUYSX8.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name... | ITB | Institut Teknologi Bandung | sandyherho | Sandy Hardian Susanto Herho | 3 | 2026-03-14T02:42:27.000Z | true | |||
2401.00368 | 2024-01-02 | Improving Text Embeddings with Large Language Models | [
"Liang Wang",
"Nan Yang",
"Xiaolong Huang",
"Linjun Yang",
"Rangan Majumder",
"Furu Wei"
] | https://github.com/kamalkraj/e5-mistral-7b-instruct | null | 84 | 15 | 85 | 2024-03-12 | null | null | null | null | 2 | 84 | true | 2024-W01 | 2024-01 | true | 1 | 8 | 3 | 50 | 5 | 219 | In this paper, we introduce a novel and simple method for obtaining
high-quality text embeddings using only synthetic data and less than 1k
training steps. Unlike existing methods that often depend on multi-stage
intermediate pre-training with billions of weakly-supervised text pairs,
followed by fine-tuning with a few... | [
{
"name": "Liang Wang",
"user": "intfloat",
"fullname": "Liang Wang",
"avatar": "/avatars/5a1ee74c2dbe349a6ec9843a1599d281.svg",
"status": "extracted_confirmed",
"hidden": true
},
{
"name": "Nan Yang",
"user": "nyanyanya",
"fullname": "nyanyanya",
"avatar": "/avatars/8137... | null | null | null | akhaliq | AK | 89 | 2023-12-31T02:13:18.000Z | true | ||
2609.34759 | 2026-09-30 | PanoVLN: Towards Effective Panoramic Vision-and-Language Navigation | [
"Zhen Wang",
"Changpeng Wang",
"Zhe Liu",
"Zhangyang Qi",
"Yuxiang Lu",
"Zimo Zeng",
"Donglian Qi",
"Xi Chen"
] | https://github.com/wangzhen-w/PanoVLN | https://wangzhen-w.github.io/PanoVLN/ | 151 | 1 | 166 | 2026-09-30 | 131 | 148 | 160 | 166 | 0 | 166 | true | 2026-W40 | 2026-09 | false | 6 | 92 | 17 | 404 | 38 | 786 | Recent vision-language models (VLMs) have advanced vision-and-language navigation (VLN), enabling models to predict navigation actions from visual observations and language instructions. In this work, we explore VLN with panoramic observations and introduce PanoVLN. The motivation is straightforward: more complete visu... | [
{
"name": "Zhen Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Changpeng Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zhe Liu",
"user": null,
... | zju | Zhejiang University | xichenhku | xichen | 62 | 2026-09-28T00:00:00.000Z | true | |||
2505.14556 | 2025-05-21 | Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI | [
"Marlène Careil",
"Yohann Benchetrit",
"Jean-Rémi King"
] | https://github.com/facebookresearch/dynadiff | null | 1 | 2 | 1 | 2025-05-21 | 0 | 1 | 1 | 1 | 0 | 1 | true | 2025-W21 | 2025-05 | false | 48 | 53 | 193 | 205 | 682 | 730 | Brain-to-image decoding has been recently propelled by the progress in
generative AI models and the availability of large ultra-high field functional
Magnetic Resonance Imaging (fMRI). However, current approaches depend on
complicated multi-stage pipelines and preprocessing steps that typically
collapse the temporal di... | [
{
"name": "Marlène Careil",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yohann Benchetrit",
"user": "ybenchetrit",
"fullname": "Yohann Benchetrit",
"avatar": "/avatars/9cba4040a9e90f2230d8b3c9412ecc26.svg",
"status": "... | null | null | null | Marl | Careil | /avatars/315c41ecad079ae57350b7662382b2cb.svg | 48 | 2025-05-20T16:14:37.000Z | false | |
2507.05169 | 2025-07-09 | Critiques of World Models | [
"Eric Xing",
"Mingkai Deng",
"Jinyu Hou",
"Zhiting Hu"
] | null | null | 27 | 1 | 27 | 2025-07-09 | 12 | 16 | 20 | 22 | 0 | 22 | true | 2025-W28 | 2025-07 | false | 10 | 28 | 38 | 99 | 145 | 383 | World Model, the supposed algorithmic surrogate of the real-world environment
which biological agents experience with and act upon, has been an emerging
topic in recent years because of the rising needs to develop virtual agents
with artificial (general) intelligence. There has been much debate on what a
world model re... | [
{
"name": "Eric Xing",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Mingkai Deng",
"user": "mingkaid",
"fullname": "Mingkai Deng",
"avatar": "/avatars/9f426e0f1ca734fb428a22881d2e7b20.svg",
"status": "claimed_verified",... | null | null | null | mingkaid | Mingkai Deng | /avatars/9f426e0f1ca734fb428a22881d2e7b20.svg | null | 2025-07-07T16:23:46.000Z | true | |
2602.04802 | 2026-02-11 | VISTA-Bench: Do Vision-Language Models Really Understand Visualized Text as Well as Pure Text? | [
"Qing'an Liu",
"Juntong Feng",
"Yuhao Wang",
"Xinzhe Han",
"Yujie Cheng",
"Yue Zhu",
"Haiwen Diao",
"Yunzhi Zhuge",
"Huchuan Lu"
] | https://github.com/QingAnLiu/VISTA-Bench | null | 2 | 3 | 2 | 2026-02-11 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2026-W07 | 2026-02 | false | 49 | 57 | 218 | 247 | 675 | 785 | Vision-Language Models (VLMs) have achieved impressive performance in cross-modal understanding across textual and visual inputs, yet existing benchmarks predominantly focus on pure-text queries. In real-world scenarios, language also frequently appears as visualized text embedded in images, raising the question of whe... | [
{
"name": "Qing'an Liu",
"user": "liuqa",
"fullname": "liuqingan",
"avatar": "/avatars/c7810a5658681f448c541af7363efbce.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Juntong Feng",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | liuqa | liuqingan | /avatars/c7810a5658681f448c541af7363efbce.svg | 14 | 2026-02-04T17:48:55.000Z | true | |
2412.14015 | 2024-12-19 | Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation | [
"Haotong Lin",
"Sida Peng",
"Jingxiao Chen",
"Songyou Peng",
"Jiaming Sun",
"Minghuan Liu",
"Hujun Bao",
"Jiashi Feng",
"Xiaowei Zhou",
"Bingyi Kang"
] | https://github.com/DepthAnything/PromptDA | null | 12 | 4 | 12 | 2024-12-19 | 9 | 11 | 11 | 12 | 0 | 12 | true | 2024-W51 | 2024-12 | false | 12 | 22 | 44 | 98 | 205 | 392 | Prompts play a critical role in unleashing the power of language and vision
foundation models for specific tasks. For the first time, we introduce
prompting into depth foundation models, creating a new paradigm for metric
depth estimation termed Prompt Depth Anything. Specifically, we use a low-cost
LiDAR as the prompt... | [
{
"name": "Haotong Lin",
"user": "haotongl",
"fullname": "Haotong Lin",
"avatar": "/avatars/f7a0fc6816535945e11bac1212dd7b57.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Sida Peng",
"user": "pengsida",
"fullname": "Sida Peng",
"avatar": "/avatars/83944d... | null | null | null | bykang | Bingyi Kang | 1,168 | 2024-12-18T16:32:12.000Z | true | ||
2512.08309 | 2025-12-10 | Terrain Diffusion: A Diffusion-Based Successor to Perlin Noise in Infinite, Real-Time Terrain Generation | [
"Alexander Goslin"
] | https://github.com/xandergos/terrain-diffusion | https://xandergos.github.io/terrain-diffusion/ | 10 | 2 | 10 | 2025-12-11 | null | 2 | 2 | 2 | 0 | 2 | true | 2025-W50 | 2025-12 | false | 20 | 27 | 107 | 130 | 525 | 633 | For decades, procedural worlds have been built on procedural noise functions such as Perlin noise, which are fast and infinite, yet fundamentally limited in realism and large-scale coherence. We introduce Terrain Diffusion, an AI-era successor to Perlin noise that bridges the fidelity of diffusion models with the prope... | [
{
"name": "Alexander Goslin",
"user": "xandergos",
"fullname": "Alexander Goslin",
"avatar": "/avatars/c94f91892070f08eb1d1b54df978cafa.svg",
"status": "claimed_verified",
"hidden": false
}
] | null | null | null | xandergos | Alexander Goslin | /avatars/c94f91892070f08eb1d1b54df978cafa.svg | 1,418 | 2025-12-09T07:10:35.000Z | true | |
2510.13678 | 2025-10-16 | FlashWorld: High-quality 3D Scene Generation within Seconds | [
"Xinyang Li",
"Tengfei Wang",
"Zixiao Gu",
"Shengchuan Zhang",
"Chunchao Guo",
"Liujuan Cao"
] | https://github.com/imlixinyang/FlashWorld | https://imlixinyang.github.io/FlashWorld-Project-Page/ | 74 | 2 | 74 | 2025-10-16 | 53 | 61 | 63 | 67 | 0 | 67 | true | 2025-W42 | 2025-10 | false | 1 | 43 | 15 | 244 | 54 | 945 | We propose FlashWorld, a generative model that produces 3D scenes from a
single image or text prompt in seconds, 10~100times faster than previous
works while possessing superior rendering quality. Our approach shifts from the
conventional multi-view-oriented (MV-oriented) paradigm, which generates
multi-view images for... | [
{
"name": "Xinyang Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Tengfei Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zixiao Gu",
"user": "nigh... | null | null | null | imlixinyang | Xinyang Li | /avatars/0ae1080eebce0f747f650bfc292c46ca.svg | 858 | 2025-10-15T15:35:48.000Z | false | |
2601.05167 | 2026-01-09 | RelayLLM: Efficient Reasoning via Collaborative Decoding | [
"Chengsong Huang",
"Tong Zheng",
"Langlin Huang",
"Jinyuan Li",
"Haolin Liu",
"Jiaxin Huang"
] | https://github.com/Chengsong-Huang/RelayLLM | null | 30 | 3 | 31 | 2026-01-09 | 18 | 23 | 26 | 27 | 0 | 27 | true | 2026-W02 | 2026-01 | false | 6 | 33 | 35 | 120 | 149 | 573 | Large Language Models (LLMs) for complex reasoning is often hindered by high computational costs and latency, while resource-efficient Small Language Models (SLMs) typically lack the necessary reasoning capacity. Existing collaborative approaches, such as cascading or routing, operate at a coarse granularity by offload... | [
{
"name": "Chengsong Huang",
"user": "ChengsongHuang",
"fullname": "Chengsong Huang",
"avatar": "/avatars/70af83e0e267be39fcd5f23b85e2dafa.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Tong Zheng",
"user": null,
"fullname": null,
"avatar": null,
"s... | null | null | null | ChengsongHuang | Chengsong Huang | /avatars/70af83e0e267be39fcd5f23b85e2dafa.svg | 41 | 2026-01-08T17:56:16.000Z | true | |
2507.17512 | 2025-07-24 | Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning | [
"Yu Li",
"Zhuoshi Pan",
"Honglin Lin",
"Mengyuan Sun",
"Conghui He",
"Lijun Wu"
] | https://github.com/Leey21/A-Data-Centric-Study | null | 37 | 1 | 37 | 2025-07-24 | 23 | 30 | 31 | 33 | 0 | 33 | true | 2025-W30 | 2025-07 | false | 4 | 11 | 24 | 86 | 97 | 383 | Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a
powerful paradigm for enhancing the reasoning capabilities of LLMs. Existing
research has predominantly concentrated on isolated reasoning domains such as
mathematical problem-solving, coding tasks, or logical reasoning. However, real
world reasonin... | [
{
"name": "Yu Li",
"user": "yu0226",
"fullname": "YU LI",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/671b852aa4fa4f8f5fb5404c/TDLsgP8WgKW-qaA8Ys-iJ.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Zhuoshi Pan",
"user": null,
"fullname"... | null | null | null | yu0226 | YU LI | 18 | 2025-07-23T13:51:04.000Z | true | ||
2411.00743 | 2024-11-05 | Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models | [
"Aashiq Muhamed",
"Mona Diab",
"Virginia Smith"
] | null | null | 7 | 2 | 7 | 2024-11-05 | 5 | 6 | 6 | 6 | 0 | 6 | true | 2024-W45 | 2024-11 | false | 19 | 23 | 64 | 76 | 224 | 285 | Understanding and mitigating the potential risks associated with foundation
models (FMs) hinges on developing effective interpretability methods. Sparse
Autoencoders (SAEs) have emerged as a promising tool for disentangling FM
representations, but they struggle to capture rare, yet crucial concepts in the
data. We intr... | [
{
"name": "Aashiq Muhamed",
"user": "aashiqmuhamed",
"fullname": "Aashiq Muhamed",
"avatar": "/avatars/2c50590905f4bd398a4c9991e1b4b5bb.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Mona Diab",
"user": null,
"fullname": null,
"avatar": null,
"status"... | null | null | null | aashiqmuhamed | Aashiq Muhamed | /avatars/2c50590905f4bd398a4c9991e1b4b5bb.svg | null | 2024-11-01T17:09:34.000Z | true | |
2602.23280 | 2026-03-09 | Physics Informed Viscous Value Representations | [
"Hrishikesh Viswanath",
"Juanwu Lu",
"S. Talha Bukhari",
"Damon Conover",
"Ziran Wang",
"Aniket Bera"
] | https://github.com/HrishikeshVish/phys-fk-value-GCRL | null | 1 | 2 | 1 | 2026-03-09 | 0 | 1 | 1 | 1 | 0 | 1 | true | 2026-W11 | 2026-03 | false | 22 | 31 | 152 | 187 | 655 | 745 | Offline goal-conditioned reinforcement learning (GCRL) learns goal-conditioned policies from static pre-collected datasets. However, accurate value estimation remains a challenge due to the limited coverage of the state-action space. Recent physics-informed approaches have sought to address this by imposing physical an... | [
{
"name": "Hrishikesh Viswanath",
"user": "hrishivish23",
"fullname": "Hrishikesh Viswanath",
"avatar": "/avatars/ef0c0b056622b83784237803eb1521a1.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Juanwu Lu",
"user": "ChocolateDave",
"fullname": "Juanwu Lu",
... | Purdue | Purdue University | hrishivish23 | Hrishikesh Viswanath | /avatars/ef0c0b056622b83784237803eb1521a1.svg | 2 | 2026-02-26T17:53:46.000Z | true | ||
2307.15504 | 2023-07-31 | Exploring Format Consistency for Instruction Tuning | [
"Shihao Liang",
"Kunlun Zhu",
"Runchu Tian",
"Yujia Qin",
"Huadong Wang",
"Xin Cong",
"Zhiyuan Liu",
"Xiaojiang Liu",
"Maosong Sun"
] | https://github.com/thunlp/unifiedinstructiontuning | null | 8 | 0 | 8 | 2024-03-12 | null | null | null | null | 0 | 8 | true | 2023-W31 | 2023-07 | true | 6 | 7 | 35 | 42 | 126 | 184 | Instruction tuning has emerged as a promising approach to enhancing large
language models in following human instructions. It is shown that increasing
the diversity and number of instructions in the training data can consistently
enhance generalization performance, which facilitates a recent endeavor to
collect various... | [
{
"name": "Shihao Liang",
"user": "pooruss",
"fullname": "Shihao Liang",
"avatar": "/avatars/f729f0bdcfbd971babfa760d8de8403c.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Kunlun Zhu",
"user": "KunlunZhu",
"fullname": "KunlunZhu",
"avatar": "/avatars/ccb... | null | null | null | akhaliq | AK | 5 | 2023-07-28T12:00:13.000Z | false | ||
2510.00184 | 2025-10-02 | Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls | [
"Xiaoyan Bai",
"Itamar Pres",
"Yuntian Deng",
"Chenhao Tan",
"Stuart Shieber",
"Fernanda Viégas",
"Martin Wattenberg",
"Andrew Lee"
] | https://github.com/ajyl/icot | null | 17 | 3 | 17 | 2025-10-02 | 13 | 13 | 13 | 15 | 0 | 15 | true | 2025-W40 | 2025-10 | false | 11 | 36 | 101 | 275 | 339 | 945 | Language models are increasingly capable, yet still fail at a seemingly
simple task of multi-digit multiplication. In this work, we study why, by
reverse-engineering a model that successfully learns multiplication via
implicit chain-of-thought, and report three findings: (1) Evidence of
long-range structure: Logit attr... | [
{
"name": "Xiaoyan Bai",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Itamar Pres",
"user": "ipres",
"fullname": "Itamar Pres",
"avatar": "/avatars/2007a6b98b0db171be091a3cf31c72ac.svg",
"status": "claimed_verified",
... | null | null | null | yuntian-deng | Yuntian Deng | 10 | 2025-09-30T19:03:26.000Z | true | ||
2509.24709 | 2025-09-30 | IWR-Bench: Can LVLMs reconstruct interactive webpage from a user interaction video? | [
"Yang Chen",
"Minghao Liu",
"Yufan Shen",
"Yunwen Li",
"Tianyuan Huang",
"Xinyu Fang",
"Tianyu Zheng",
"Wenxuan Huang",
"Cheng Yang",
"Daocheng Fu",
"Jianbiao Mei",
"Rong Wu",
"Licheng Wen",
"Xuemeng Yang",
"Song Mao",
"Qunshu Lin",
"Zhi Yu",
"Yongliang Shen",
"Yu Qiao",
"Botia... | https://github.com/SIGMME/IWR-Bench | https://l-o-i.github.io/IWR-Bench/ | 7 | 1 | 7 | 2025-09-30 | 1 | 2 | 3 | 3 | 0 | 3 | true | 2025-W40 | 2025-09 | false | 64 | 82 | 198 | 275 | 407 | 536 | The webpage-to-code task requires models to understand visual representations
of webpages and generate corresponding code. However, existing benchmarks
primarily focus on static screenshot-to-code tasks, thereby overlooking the
dynamic interactions fundamental to real-world web applications. To address
this limitation,... | [
{
"name": "Yang Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Minghao Liu",
"user": "Liam-Liu",
"fullname": "minghao",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6417d9ea8f689506e7148417/bAYcr... | IWR-Bench | IWR-Bench Team | taesiri | taesiri | 23 | 2025-09-29T12:38:06.000Z | false | |||
2410.02525 | 2024-10-04 | Contextual Document Embeddings | [
"John X. Morris",
"Alexander M. Rush"
] | null | null | 23 | 4 | 24 | 2024-10-04 | 2 | 6 | 8 | 14 | 1 | 14 | true | 2024-W40 | 2024-10 | false | 13 | 27 | 38 | 88 | 184 | 482 | Dense document embeddings are central to neural retrieval. The dominant
paradigm is to train and construct embeddings by running encoders directly on
individual documents. In this work, we argue that these embeddings, while
effective, are implicitly out-of-context for targeted use cases of retrieval,
and that a context... | [
{
"name": "John X. Morris",
"user": "jxm",
"fullname": "Jack Morris",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1652114014657-5edc0500968f6028e0559ff8.jpeg",
"status": "extracted_pending",
"hidden": false
},
{
"name": "Alexander M. Rush",
"user": null,
... | null | null | null | jxm | Jack Morris | null | 2024-10-03T14:33:34.000Z | true | ||
2509.05668 | 2025-09-09 | Llama-GENBA-10B: A Trilingual Large Language Model for German, English and Bavarian | [
"Michael Hoffmann",
"Jophin John",
"Stefan Schweter",
"Gokul Ramakrishnan",
"Hoi-Fong Mak",
"Alice Zhang",
"Dmitry Gaynullin",
"Nicolay J. Hammer"
] | null | null | 8 | 6 | 8 | 2025-09-09 | 3 | 4 | 4 | 5 | 0 | 5 | true | 2025-W37 | 2025-09 | false | 17 | 25 | 67 | 92 | 359 | 536 | We present Llama-GENBA-10B, a trilingual foundation model addressing
English-centric bias in large language models. Built on Llama 3.1-8B and scaled
to 10B parameters, Llama-GENBA-10B is continuously pretrained on 164B tokens
(82B English, 82B German, and 80M Bavarian), balancing resources while
preventing English domi... | [
{
"name": "Michael Hoffmann",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jophin John",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Stefan Schweter",
"u... | null | null | null | stefan-it | Stefan Schweter | null | 2025-09-06T10:12:52.000Z | true | ||
2601.02256 | 2026-01-06 | VAR RL Done Right: Tackling Asynchronous Policy Conflicts in Visual Autoregressive Generation | [
"Shikun Sun",
"Liao Qu",
"Huichao Zhang",
"Yiheng Liu",
"Yangyang Song",
"Xian Li",
"Xu Wang",
"Yi Jiang",
"Daniel K. Du",
"Xinglong Wu",
"Jia Jia"
] | null | https://github.com/ByteVisionLab/NextFlow | 33 | 3 | 33 | 2026-01-06 | 28 | 30 | 30 | 32 | 0 | 32 | true | 2026-W02 | 2026-01 | false | 6 | 25 | 27 | 120 | 131 | 573 | Visual generation is dominated by three paradigms: AutoRegressive (AR), diffusion, and Visual AutoRegressive (VAR) models. Unlike AR and diffusion, VARs operate on heterogeneous input structures across their generation steps, which creates severe asynchronous policy conflicts. This issue becomes particularly acute in r... | [
{
"name": "Shikun Sun",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Liao Qu",
"user": "leo1117",
"fullname": "Liao Qu",
"avatar": "/avatars/51af43cab078705b8745b4f942f542e5.svg",
"status": "claimed_verified",
"hidd... | ByteDance | ByteDance | leo1117 | Liao Qu | /avatars/51af43cab078705b8745b4f942f542e5.svg | null | 2026-01-05T16:36:40.000Z | true | ||
2406.20095 | 2024-07-01 | LLaRA: Supercharging Robot Learning Data for Vision-Language Policy | [
"Xiang Li",
"Cristina Mata",
"Jongwoo Park",
"Kumara Kahatapitiya",
"Yoo Sung Jang",
"Jinghuan Shang",
"Kanchana Ranasinghe",
"Ryan Burgert",
"Mu Cai",
"Yong Jae Lee",
"Michael S. Ryoo"
] | https://github.com/LostXine/LLaRA | https://github.com/LostXine/LLaRA | 18 | 1 | 18 | 2024-07-01 | 14 | 16 | 16 | 17 | 0 | 17 | true | 2024-W27 | 2024-07 | false | 4 | 11 | 27 | 62 | 134 | 345 | Large Language Models (LLMs) equipped with extensive world knowledge and
strong reasoning skills can tackle diverse tasks across domains, often by
posing them as conversation-style instruction-response pairs. In this paper, we
propose LLaRA: Large Language and Robotics Assistant, a framework which
formulates robot acti... | [
{
"name": "Xiang Li",
"user": "variante",
"fullname": "Xiang Li",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6369c6b17f319ce3573771ae/g7zVTXWBeeOBQqR5mOByS.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Cristina Mata",
"user": "cfmata"... | null | null | null | variante | Xiang Li | 228 | 2024-06-28T17:59:12.000Z | true | ||
2407.07304 | 2024-07-11 | Inference Performance Optimization for Large Language Models on CPUs | [
"Pujiang He",
"Shan Zhou",
"Wenhuan Huang",
"Changqing Li",
"Duyi Wang",
"Bin Guo",
"Chen Meng",
"Sheng Gui",
"Weifei Yu",
"Yi Xie"
] | https://github.com/intel/xfastertransformer | null | 53 | 7 | 54 | 2024-07-11 | 5 | 37 | 42 | 47 | 1 | 47 | true | 2024-W28 | 2024-07 | false | 2 | 14 | 4 | 83 | 20 | 345 | Large language models (LLMs) have shown exceptional performance and vast
potential across diverse tasks. However, the deployment of LLMs with high
performance in low-resource environments has garnered significant attention in
the industry. When GPU hardware resources are limited, we can explore
alternative options on C... | [
{
"name": "Pujiang He",
"user": "pujiang",
"fullname": "pujiang",
"avatar": "/avatars/dad07355462c1a7e296af237fb55a6fc.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Shan Zhou",
"user": "ShanShanZhou",
"fullname": "Shan Zhou",
"avatar": "/avatars/710f1570... | null | null | null | akhaliq | AK | 435 | 2024-07-10T01:53:49.000Z | true | ||
2601.07632 | 2026-01-14 | GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models | [
"Zhankai Ye",
"Bofan Li",
"Yukai Jin",
"Shuoqiu Li",
"Wei Wang",
"Yanfu Zhang",
"Shangqian Gao",
"Xin Liu"
] | https://github.com/JYe16/GeoMotionGPT | null | 1 | 2 | 2 | 2026-01-14 | 1 | 1 | 1 | 1 | 1 | 1 | true | 2026-W03 | 2026-01 | false | 24 | 24 | 142 | 162 | 519 | 573 | Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-language reasoning. However, existing pipelines typically decouple motion quantization from semantic embedding learning, linking them solely via token IDs. This approach fai... | [
{
"name": "Zhankai Ye",
"user": "zy22b",
"fullname": "Zhankai Ye",
"avatar": "/avatars/8f4ddca4ef47e07389a93ed126d8ffb6.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Bofan Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hi... | FloridaStateUniversity | Florida State University | zy22b | Zhankai Ye | /avatars/8f4ddca4ef47e07389a93ed126d8ffb6.svg | 8 | 2026-01-12T15:14:29.000Z | true | ||
2512.02008 | 2025-12-02 | The Art of Scaling Test-Time Compute for Large Language Models | [
"Aradhye Agarwal",
"Ayan Sengupta",
"Tanmoy Chakraborty"
] | https://github.com/Aradhye2002/art_of_tts | null | 6 | 2 | 6 | 2025-12-02 | 2 | 2 | 2 | 2 | 0 | 2 | true | 2025-W49 | 2025-12 | false | 36 | 47 | 154 | 191 | 525 | 633 | Test-time scaling (TTS) -- the dynamic allocation of compute during inference -- is a promising direction for improving reasoning in large language models (LLMs). However, a systematic comparison of well-known TTS strategies under identical conditions is missing, and the influence of model type and problem difficulty o... | [
{
"name": "Aradhye Agarwal",
"user": "aradhye",
"fullname": "Aradhye Agarwal",
"avatar": "/avatars/816a962c62c805adf7789fa8e398b01e.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ayan Sengupta",
"user": null,
"fullname": null,
"avatar": null,
"statu... | null | null | null | aradhye | Aradhye Agarwal | /avatars/816a962c62c805adf7789fa8e398b01e.svg | 4 | 2025-12-01T18:59:28.000Z | true | |
2507.18546 | 2025-07-25 | GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface | [
"Urchade Zaratiana",
"Gil Pasternak",
"Oliver Boyd",
"George Hurn-Maloney",
"Ash Lewis"
] | https://github.com/fastino-ai/GLiNER2 | null | 43 | 12 | 43 | 2025-07-25 | 4 | 11 | 12 | 13 | 0 | 13 | true | 2025-W30 | 2025-07 | false | 9 | 21 | 49 | 86 | 209 | 383 | Information extraction (IE) is fundamental to numerous NLP applications, yet
existing solutions often require specialized models for different tasks or rely
on computationally expensive large language models. We present GLiNER2, a
unified framework that enhances the original GLiNER architecture to support
named entity ... | [
{
"name": "Urchade Zaratiana",
"user": "urchade",
"fullname": "Urchade Zaratiana",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/62111fdbe1d974ee5bcbfa27/YUzX6lBvW8pbxDorx1kgV.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Gil Pasternak",
... | null | null | null | stefan-it | Stefan Schweter | 2,319 | 2025-07-24T16:11:14.000Z | true | ||
2410.08565 | 2024-10-14 | Baichuan-Omni Technical Report | [
"Yadong Li",
"Haoze Sun",
"Mingan Lin",
"Tianpeng Li",
"Guosheng Dong",
"Tao Zhang",
"Bowen Ding",
"Wei Song",
"Zhenglin Cheng",
"Yuqi Huo",
"Song Chen",
"Xu Li",
"Da Pan",
"Shusen Zhang",
"Xin Wu",
"Zheng Liang",
"Jun Liu",
"Tao Zhang",
"Keer Lu",
"Yaqi Zhao",
"Yanjun Shen",... | https://github.com/westlake-baichuan-mllm/bc-omni | null | 79 | 8 | 89 | 2024-10-14 | 60 | 75 | 80 | 80 | 10 | 80 | true | 2024-W42 | 2024-10 | false | 1 | 20 | 2 | 117 | 7 | 482 | The salient multimodal capabilities and interactive experience of GPT-4o
highlight its critical role in practical applications, yet it lacks a
high-performing open-source counterpart. In this paper, we introduce
Baichuan-Omni, the first open-source 7B Multimodal Large Language Model (MLLM)
adept at concurrently process... | [
{
"name": "Yadong Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Haoze Sun",
"user": "AlvinSunYooo",
"fullname": "Alvin Sun",
"avatar": "/avatars/df17b66780e14e07bbe4625f068a94ad.svg",
"status": "claimed_verified",
... | null | null | null | kenshinn | Zhenglin Cheng | /avatars/86a748a3264e6e0f4ee5eaf8f7032ecb.svg | 272 | 2024-10-11T06:44:31.000Z | true | |
2504.12080 | 2025-04-28 | DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency | [
"Mengshi Qi",
"Pengfei Zhu",
"Xiangtai Li",
"Xiaoyang Bi",
"Lu Qi",
"Huadong Ma",
"Ming-Hsuan Yang"
] | https://github.com/zaplm/dc-sam | null | 8 | 2 | 8 | 2025-04-28 | 6 | 7 | 7 | 7 | 0 | 7 | true | 2025-W18 | 2025-04 | false | 12 | 12 | 54 | 72 | 337 | 456 | Given a single labeled example, in-context segmentation aims to segment
corresponding objects. This setting, known as one-shot segmentation in few-shot
learning, explores the segmentation model's generalization ability and has been
applied to various vision tasks, including scene understanding and image/video
editing. ... | [
{
"name": "Mengshi Qi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Pengfei Zhu",
"user": "zaplm",
"fullname": "Pengfei Zhu",
"avatar": "/avatars/5c43b7b50aeb3d1459307334ddcd1d1b.svg",
"status": "claimed_verified",
... | null | null | null | zaplm | Pengfei Zhu | /avatars/5c43b7b50aeb3d1459307334ddcd1d1b.svg | 58 | 2025-04-16T13:41:59.000Z | true | |
2604.01483 | 2026-04-07 | Type-Checked Compliance: Deterministic Guardrails for Agentic Financial Systems Using Lean 4 Theorem Proving | [
"Devakh Rashie",
"Veda Rashi"
] | https://github.com/arkanemystic/lean-agent-protocol | https://axiom.devrashie.space | 2 | 2 | 7 | 2026-04-07 | 1 | 4 | 5 | 7 | 5 | 7 | true | 2026-W15 | 2026-04 | false | 32 | 37 | 123 | 155 | 422 | 707 | The rapid evolution of autonomous, agentic artificial intelligence within financial services has introduced an existential architectural crisis: large language models (LLMs) are probabilistic, non-deterministic systems operating in domains that demand absolute, mathematically verifiable compliance guarantees. Existing ... | [
{
"name": "Devakh Rashie",
"user": "arkanemystic",
"fullname": "Devakh Rashie",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6918bd7f0dc2cd15ede7e659/AADjFYnUZJdj9ofY97BnM.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Veda Rashi",
"user... | null | null | null | arkanemystic | Devakh Rashie | 15 | 2026-04-01T00:00:00.000Z | true | ||
2506.01004 | 2025-06-04 | Motion-Aware Concept Alignment for Consistent Video Editing | [
"Tong Zhang",
"Juan C Leon Alcazar",
"Bernard Ghanem"
] | https://github.com/ZhangT-tech/MoCA-Video | https://zhangt-tech.github.io/MoCA-Page/ | 8 | 2 | 8 | 2025-06-04 | 3 | 7 | 7 | 7 | 0 | 7 | true | 2025-W23 | 2025-06 | false | 28 | 50 | 129 | 250 | 376 | 679 | We introduce MoCA-Video (Motion-Aware Concept Alignment in Video), a
training-free framework bridging the gap between image-domain semantic mixing
and video. Given a generated video and a user-provided reference image,
MoCA-Video injects the semantic features of the reference image into a specific
object within the vid... | [
{
"name": "Tong Zhang",
"user": "Tong98Zhang",
"fullname": "Tong Zhang",
"avatar": "/avatars/dde3c047e627bacd69e0f063a4a833b2.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Juan C Leon Alcazar",
"user": null,
"fullname": null,
"avatar": null,
"statu... | null | null | null | Tong98Zhang | Tong Zhang | /avatars/dde3c047e627bacd69e0f063a4a833b2.svg | null | 2025-06-01T13:28:04.000Z | true | |
2510.02283 | 2025-10-03 | Self-Forcing++: Towards Minute-Scale High-Quality Video Generation | [
"Justin Cui",
"Jie Wu",
"Ming Li",
"Tao Yang",
"Xiaojie Li",
"Rui Wang",
"Andrew Bai",
"Yuanhao Ban",
"Cho-Jui Hsieh"
] | https://github.com/justincui03/Self-Forcing-Plus-Plus | https://self-forcing-plus-plus.github.io/ | 98 | 3 | 98 | 2025-10-03 | 58 | 66 | 74 | 86 | 0 | 86 | true | 2025-W40 | 2025-10 | false | 2 | 52 | 11 | 275 | 38 | 945 | Diffusion models have revolutionized image and video generation, achieving
unprecedented visual quality. However, their reliance on transformer
architectures incurs prohibitively high computational costs, particularly when
extending generation to long videos. Recent work has explored autoregressive
formulations for lon... | [
{
"name": "Justin Cui",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jie Wu",
"user": "wujie10",
"fullname": "wujie10558@gmail.com",
"avatar": "/avatars/731467e2d80d0ae163c4a00a9e3ff9e5.svg",
"status": "claimed_verified... | ByteDance-Seed | ByteDance Seed | cuijiaxing | cuijiaxing | /avatars/b2a1b939f3112b476e7641e0c5fd2dc7.svg | 273 | 2025-10-02T17:55:42.000Z | false | ||
2401.10889 | 2024-01-22 | Synthesizing Moving People with 3D Control | [
"Boyi Li",
"Jathushan Rajasegaran",
"Yossi Gandelsman",
"Alexei A. Efros",
"Jitendra Malik"
] | null | null | 12 | 1 | 12 | 2024-03-12 | null | null | null | null | 0 | 12 | true | 2024-W04 | 2024-01 | true | 5 | 8 | 33 | 55 | 152 | 219 | In this paper, we present a diffusion model-based framework for animating
people from a single image for a given target 3D motion sequence. Our approach
has two core components: a) learning priors about invisible parts of the human
body and clothing, and b) rendering novel body poses with proper clothing and
texture. F... | [
{
"name": "Boyi Li",
"user": "Boyiliee",
"fullname": "Boyi Li",
"avatar": "/avatars/af04728788d78fe7d6375e19e32a535e.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Jathushan Rajasegaran",
"user": "brjathu",
"fullname": "Jathushan Rajasegaran",
"avatar": "... | null | null | null | akhaliq | AK | null | 2024-01-19T18:59:11.000Z | false | ||
2511.06309 | 2025-11-11 | The Station: An Open-World Environment for AI-Driven Discovery | [
"Stephen Chung",
"Wenyu Du"
] | https://github.com/dualverse-ai/station_data | https://dualverse-ai.github.io/station_data/ | 37 | 5 | 37 | 2025-11-11 | 28 | 31 | 34 | 34 | 0 | 34 | true | 2025-W46 | 2025-11 | false | 5 | 31 | 21 | 86 | 87 | 412 | We introduce the STATION, an open-world multi-agent environment that models a
miniature scientific ecosystem. Leveraging their extended context windows,
agents in the Station can engage in long scientific journeys that include
reading papers from peers, formulating hypotheses, submitting code, performing
analyses, and ... | [
{
"name": "Stephen Chung",
"user": "stephenchungmh",
"fullname": "Stephen Chung",
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"status": "claimed_verified",
"hidden": false
},
{
"name": "Wenyu Du",
"user"... | null | null | null | taesiri | taesiri | 4 | 2025-11-09T10:13:00.000Z | true | ||
2604.18543 | 2026-04-21 | ClawEnvKit: Automatic Environment Generation for Claw-Like Agents | [
"Xirui Li",
"Ming Li",
"Derry Xu",
"Wei-Lin Chiang",
"Ion Stoica",
"Cho-Jui Hsieh",
"Tianyi Zhou"
] | https://github.com/xirui-li/ClawEnvKit | null | 30 | 2 | 31 | 2026-04-21 | 17 | 21 | 26 | 28 | 1 | 28 | true | 2026-W17 | 2026-04 | false | 7 | 49 | 24 | 166 | 160 | 707 | Constructing environments for training and evaluating claw-like agents remains a manual, human-intensive process that does not scale. We argue that what is needed is not just a dataset, but an automated pipeline capable of generating diverse, verified environments on demand. To this end, we introduce ClawEnvKit, an aut... | [
{
"name": "Xirui Li",
"user": "AIcell",
"fullname": "Xirui Li",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6534a434e778506c5b1e5be8/349SdAnjEdIQJSzWvKfZ4.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ming Li",
"user": null,
"fullna... | umd-zhou-lab | Tianyi Lab | taesiri | taesiri | 62 | 2026-04-20T00:00:00.000Z | true | |||
2606.04048 | 2026-06-04 | Unlocking Feature Learning in Gated Delta Networks at Scale | [
"Yifeng Liu",
"Quanquan Gu"
] | https://github.com/lauyikfung/gated_delta_net_mup | null | 2 | 2 | 3 | 2026-06-04 | 2 | 2 | 2 | 2 | 1 | 2 | true | 2026-W23 | 2026-06 | false | 40 | 54 | 220 | 280 | 787 | 946 | Training and scaling Large Language Models demand enormous computational resources, motivating both efficient sub-quadratic architectures and principled hyperparameter tuning methods. While the Maximal Update Parametrization (μP) has enabled zero-shot hyperparameter transfer for standard Transformers, its extension to ... | [
{
"name": "Yifeng Liu",
"user": "Lewis-Lau",
"fullname": "Yifeng Liu",
"avatar": "/avatars/56601a25e5f883a8f6dc15f6fd9dcc57.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Quanquan Gu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | UCLA | University of California, Los Angeles | Lewis-Lau | Yifeng Liu | /avatars/56601a25e5f883a8f6dc15f6fd9dcc57.svg | 1 | 2026-06-02T00:00:00.000Z | true | ||
2501.13920 | 2025-01-24 | IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models | [
"Jiayi Lei",
"Renrui Zhang",
"Xiangfei Hu",
"Weifeng Lin",
"Zhen Li",
"Wenjian Sun",
"Ruoyi Du",
"Le Zhuo",
"Zhongyu Li",
"Xinyue Li",
"Shitian Zhao",
"Ziyu Guo",
"Yiting Lu",
"Peng Gao",
"Hongsheng Li"
] | https://github.com/jylei16/Imagine-e | null | 19 | 2 | 19 | 2025-01-24 | 8 | 11 | 12 | 13 | 0 | 13 | true | 2025-W04 | 2025-01 | false | 8 | 17 | 38 | 59 | 165 | 266 | With the rapid development of diffusion models, text-to-image(T2I) models
have made significant progress, showcasing impressive abilities in prompt
following and image generation. Recently launched models such as FLUX.1 and
Ideogram2.0, along with others like Dall-E3 and Stable Diffusion 3, have
demonstrated exceptiona... | [
{
"name": "Jiayi Lei",
"user": "jyjyjyjy",
"fullname": "jiayi lei",
"avatar": "/avatars/af1ad5048eaa9dc417837ad02f927911.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Renrui Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | s-emanuilov | Simeon Emanuilov | 14 | 2025-01-23T18:58:33.000Z | false | ||
2607.13918 | 2026-07-20 | Partially Correlated Verifier Cascades in LLM Harnesses: Concave Log-Odds, Polynomial Reliability, and Blind-Spot Ceilings | [
"Jiangang Han"
] | https://github.com/jianganghan/harness-verifier-cascades | null | 2 | 2 | 3 | 2026-07-21 | null | 1 | 1 | 2 | 1 | 2 | true | 2026-W30 | 2026-07 | false | 25 | 26 | 124 | 130 | 585 | 601 | Serial verification gates are a core reliability primitive in LLM harnesses: a candidate answer is returned only if k verifier calls all accept it. Under conditionally independent gates, the recent Odds Law (arXiv:2606.15712) shows that posterior log-odds grow linearly in k, so failure decays exponentially, and states ... | [
{
"name": "Jiangang Han",
"user": "jianganghan",
"fullname": "Jiangang Han",
"avatar": "/avatars/0cc2d589dc08c66cecf514ee894d42cf.svg",
"status": "claimed_verified",
"hidden": false
}
] | null | null | null | jianganghan | Jiangang Han | /avatars/0cc2d589dc08c66cecf514ee894d42cf.svg | null | 2026-07-15T00:00:00.000Z | true | |
2608.10366 | 2026-08-12 | DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments? | [
"Mizanur Rahman",
"Mohammed Saidul Islam",
"Ridwan Mahbub",
"Md Tahmid Rahman Laskar",
"Shafiq Joty",
"Enamul Hoque Prince"
] | https://github.com/vis-nlp/DSAgentBench | null | 11 | 1 | 11 | 2026-08-12 | 2 | 8 | 9 | 10 | 0 | 10 | true | 2026-W33 | 2026-08 | false | 19 | 23 | 92 | 155 | 397 | 647 | Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coordinated use of tools such as notebooks, IDEs, terminals, browsers, and databases within real operating environments. Yet existing benchmarks lack real-computer interact... | [
{
"name": "Mizanur Rahman",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Mohammed Saidul Islam",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Ridwan Mahbub",
... | null | null | null | taesiri | taesiri | 4 | 2026-08-11T00:00:00.000Z | false | ||
2610.05166 | 2026-10-07 | A Safe Action Is Not Enough: Feasible-Future Decoding for Vision-Language-Action Policies | [
"Tu Nguyen",
"Matthieu Zimmer",
"Vu Anh Vu",
"Ziyi Wang",
"Jannik Hammel Nielsen",
"Xuebing Zhou",
"Haitham Bou Ammar"
] | null | https://tumeteor.github.io/safety-chores-rl/ | 3 | 3 | 3 | 2026-10-07 | 2 | 3 | 3 | 3 | 0 | 3 | true | 2026-W41 | 2026-10 | false | 60 | 73 | 335 | 362 | 943 | 1,077 | A safe action is not necessarily a viable one. A frozen vision-language-action (VLA) policy can favor a locally admissible move that leaves no policy-supported route to safe task completion. We call this the feasibility-likelihood gap: likelihood ranks the next move, while feasibility depends on the futures it leaves o... | [
{
"name": "Tu Nguyen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Matthieu Zimmer",
"user": "MatthieuZ",
"fullname": "Matthieu Zimmer",
"avatar": "/avatars/d84e497cbcd44e7e06449092033f5bbd.svg",
"status": "claimed_ver... | huawei-noah | HUAWEI Noah's Ark Lab | tumeteor | Tu Nguyen | /avatars/b1fa3ca96ce9bd3419c9c87dd57b3b9d.svg | null | 2026-10-06T00:00:00.000Z | false | ||
2610.17665 | 2026-10-16 | RoTA-Bench: Evaluating 3D Spatial Reasoning through Interactive Projection Alignment | [
"Qingchuan Ma",
"Yuexiao Ma",
"Xiang Meng",
"Yixuan Zou",
"Tianyu Xie",
"Wang Chen",
"Yuhui Zeng",
"Yuhang Wu",
"Xiawu Zheng",
"Rongrong Ji"
] | https://github.com/MAC-AutoML/RoTA-Bench | https://www.modelscope.cn/studios/san2333333/rotabench-anon?mode=full&app_path=%2Fportal | 206 | 2 | 206 | 2026-10-16 | 198 | 201 | 196 | 206 | 0 | 206 | false | 2026-W42 | 2026-10 | false | 6 | 84 | 17 | 356 | 33 | 1,077 | Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipating the effects of rotation, and refining actions through visual feedback. We introduce RoTA-Bench to evaluate these abilities through interactive 3D-to-2D projection ali... | [
{
"name": "Qingchuan Ma",
"user": "QingchuanMa",
"fullname": "Qingchuan Ma",
"avatar": "/avatars/41a8fd63d756d51c09e5894198f4883b.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Yuexiao Ma",
"user": null,
"fullname": null,
"avatar": null,
"status": n... | MAC-AutoML | MAC-AutoML | QingchuanMa | Qingchuan Ma | /avatars/41a8fd63d756d51c09e5894198f4883b.svg | 5 | 2026-10-14T00:00:00.000Z | true | ||
2511.00086 | 2025-11-04 | Generalizing Test-time Compute-optimal Scaling as an Optimizable Graph | [
"Fali Wang",
"Jihai Chen",
"Shuhua Yang",
"Runxue Bao",
"Tianxiang Zhao",
"Zhiwei Zhang",
"Xianfeng Tang",
"Hui Liu",
"Qi He",
"Suhang Wang"
] | null | null | 42 | 1 | 42 | 2025-11-04 | 32 | 38 | 40 | 40 | 0 | 40 | true | 2025-W45 | 2025-11 | false | 3 | 30 | 17 | 106 | 74 | 412 | Test-Time Scaling (TTS) improves large language models (LLMs) by allocating
additional computation during inference, typically through parallel,
sequential, or hybrid scaling. However, prior studies often assume fixed
collaboration architectures (e.g., topologies) and single-model usage,
overlooking that optimal archit... | [
{
"name": "Fali Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jihai Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Shuhua Yang",
"user": null,
... | PennState | Pennsylvania State University | https://www.gravatar.com/avatar/b3578c3ac0fec6a791bb71c68bf8a92a?d=retro&size=100 | FairyFali | Fali Wang | /avatars/c2f6507fa7dcf00fe0151462533f1c2c.svg | null | 2025-10-29T22:14:25.000Z | false | |
2306.07970 | 2023-06-14 | Neural Scene Chronology | [
"Haotong Lin",
"Qianqian Wang",
"Ruojin Cai",
"Sida Peng",
"Hadar Averbuch-Elor",
"Xiaowei Zhou",
"Noah Snavely"
] | https://github.com/zju3dv/NeuSC | null | 6 | 0 | 6 | 2024-03-12 | null | null | null | null | 0 | 6 | true | 2023-W24 | 2023-06 | true | 9 | 17 | 41 | 64 | 127 | 257 | In this work, we aim to reconstruct a time-varying 3D model, capable of
rendering photo-realistic renderings with independent control of viewpoint,
illumination, and time, from Internet photos of large-scale landmarks. The core
challenges are twofold. First, different types of temporal changes, such as
illumination and... | [
{
"name": "Haotong Lin",
"user": "haotongl",
"fullname": "Haotong Lin",
"avatar": "/avatars/f7a0fc6816535945e11bac1212dd7b57.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Qianqian Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": nul... | null | null | null | akhaliq | AK | 119 | 2023-06-13T17:59:58.000Z | false | ||
2507.07024 | 2025-07-10 | FlexOlmo: Open Language Models for Flexible Data Use | [
"Weijia Shi",
"Akshita Bhagia",
"Kevin Farhat",
"Niklas Muennighoff",
"Pete Walsh",
"Jacob Morrison",
"Dustin Schwenk",
"Shayne Longpre",
"Jake Poznanski",
"Allyson Ettinger",
"Daogao Liu",
"Margaret Li",
"Dirk Groeneveld",
"Mike Lewis",
"Wen-tau Yih",
"Luca Soldaini",
"Kyle Lo",
"... | https://github.com/allenai/FlexOlmo | https://allenai.org/blog/flexolmo | 8 | 0 | 10 | 2025-07-11 | null | 4 | 5 | 5 | 2 | 5 | true | 2025-W28 | 2025-07 | false | 15 | 22 | 75 | 99 | 304 | 383 | We introduce FlexOlmo, a new class of language models (LMs) that supports (1)
distributed training without data sharing, where different model parameters are
independently trained on closed datasets, and (2) data-flexible inference,
where these parameters along with their associated data can be flexibly
included or exc... | [
{
"name": "Weijia Shi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Akshita Bhagia",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Kevin Farhat",
"user": ... | null | null | null | Muennighoff | Niklas Muennighoff | 155 | 2025-07-09T16:54:21.000Z | false | ||
2603.29247 | 2026-04-02 | MemRerank: Preference Memory for Personalized Product Reranking | [
"Zhiyuan Peng",
"Xuyang Wu",
"Huaixiao Tou",
"Yi Fang",
"Yi Gong"
] | null | null | 4 | 2 | 6 | 2026-04-02 | 2 | 2 | 4 | 5 | 2 | 5 | true | 2026-W14 | 2026-04 | false | 24 | 30 | 141 | 168 | 508 | 707 | LLM-based shopping agents increasingly rely on long purchase histories and multi-turn interactions for personalization, yet naively appending raw history to prompts is often ineffective due to noise, length, and relevance mismatch. We propose MemRerank, a preference memory framework that distills user purchase history ... | [
{
"name": "Zhiyuan Peng",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Xuyang Wu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Huaixiao Tou",
"user": nul... | null | null | null | zhiyuanpeng | Zhiyuan Peng | /avatars/e39ca6d93cf667ec56c8519af9ec39fd.svg | null | 2026-03-31T04:16:18.000Z | false | |
2506.07803 | 2025-06-10 | Image Reconstruction as a Tool for Feature Analysis | [
"Eduard Allakhverdov",
"Dmitrii Tarasov",
"Elizaveta Goncharova",
"Andrey Kuznetsov"
] | https://github.com/FusionBrainLab/feature_analysis | https://fusionbrainlab.github.io/feature_analysis/ | 29 | 2 | 29 | 2025-06-10 | 24 | 27 | 28 | 28 | 0 | 28 | true | 2025-W24 | 2025-06 | false | 7 | 48 | 30 | 162 | 123 | 679 | Vision encoders are increasingly used in modern applications, from
vision-only models to multimodal systems such as vision-language models.
Despite their remarkable success, it remains unclear how these architectures
represent features internally. Here, we propose a novel approach for
interpreting vision features via i... | [
{
"name": "Eduard Allakhverdov",
"user": "combat-helicopter",
"fullname": "Allakhverdov Eduard",
"avatar": "/avatars/6cbac4e4be5029655702c5d8b9046b90.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Dmitrii Tarasov",
"user": null,
"fullname": null,
"avata... | null | null | null | Elizaveta | Elizaveta Goncharova | /avatars/bfd63bcd81548283f5e496e3693bf143.svg | 5 | 2025-06-09T14:32:18.000Z | false | |
2407.10973 | 2024-07-16 | Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion | [
"Yongyuan Liang",
"Tingqiang Xu",
"Kaizhe Hu",
"Guangqi Jiang",
"Furong Huang",
"Huazhe Xu"
] | null | null | 10 | 2 | 11 | 2024-07-16 | 7 | 7 | 8 | 9 | 1 | 9 | true | 2024-W29 | 2024-07 | false | 7 | 16 | 37 | 86 | 204 | 345 | Can we generate a control policy for an agent using just one demonstration of
desired behaviors as a prompt, as effortlessly as creating an image from a
textual description? In this paper, we present Make-An-Agent, a novel policy
parameter generator that leverages the power of conditional diffusion models
for behavior-... | [
{
"name": "Yongyuan Liang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Tingqiang Xu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Kaizhe Hu",
"user": n... | null | null | null | cheryyunl | Yongyuan Liang | null | 2024-07-15T17:59:57.000Z | false | ||
2410.12490 | 2024-10-17 | Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective | [
"Yongxin Zhu",
"Bocheng Li",
"Hang Zhang",
"Xin Li",
"Linli Xu",
"Lidong Bing"
] | https://github.com/DAMO-NLP-SG/DiGIT | null | 7 | 2 | 8 | 2024-10-17 | 2 | 4 | 6 | 6 | 0 | 6 | true | 2024-W42 | 2024-10 | false | 15 | 23 | 84 | 117 | 342 | 482 | Latent-based image generative models, such as Latent Diffusion Models (LDMs)
and Mask Image Models (MIMs), have achieved notable success in image generation
tasks. These models typically leverage reconstructive autoencoders like VQGAN
or VAE to encode pixels into a more compact latent space and learn the data
distribut... | [
{
"name": "Yongxin Zhu",
"user": "youngsheen",
"fullname": "yongxinzhu",
"avatar": "/avatars/661e7acbc36497e1e733715cf6ec212d.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Bocheng Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,... | null | null | null | youngsheen | yongxinzhu | /avatars/661e7acbc36497e1e733715cf6ec212d.svg | 78 | 2024-10-16T12:13:17.000Z | true | |
2503.04973 | 2025-03-11 | Beyond RAG: Task-Aware KV Cache Compression for Comprehensive Knowledge Reasoning | [
"Giulio Corallo",
"Orion Weller",
"Fabio Petroni",
"Paolo Papotti"
] | null | https://huggingface.co/spaces/giulio98/beyondrag | 27 | 7 | 27 | 2025-03-11 | 12 | 18 | 20 | 20 | 0 | 20 | true | 2025-W11 | 2025-03 | false | 11 | 50 | 49 | 175 | 167 | 611 | Incorporating external knowledge in large language models (LLMs) enhances
their utility across diverse applications, but existing methods have
trade-offs. Retrieval-Augmented Generation (RAG) fetches evidence via
similarity search, but key information may fall outside top ranked results.
Long-context models can process... | [
{
"name": "Giulio Corallo",
"user": "giulio98",
"fullname": "Giulio Corallo",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1666106981514-62c88e75a5ac2974c0a5c8ea.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Orion Weller",
"user": "orio... | SAP | SAP | giulio98 | Giulio Corallo | null | 2025-03-06T21:07:41.000Z | true | |||
2410.22901 | 2024-11-04 | HelloMeme: Integrating Spatial Knitting Attentions to Embed High-Level and Fidelity-Rich Conditions in Diffusion Models | [
"Shengkai Zhang",
"Nianhong Jiao",
"Tian Li",
"Chaojie Yang",
"Chenhui Xue",
"Boya Niu",
"Jun Gao"
] | https://github.com/HelloVision/HelloMeme | https://songkey.github.io/hellomeme/ | 7 | 2 | 8 | 2024-11-04 | 5 | 7 | 7 | 7 | 1 | 7 | true | 2024-W45 | 2024-11 | false | 13 | 19 | 61 | 76 | 211 | 285 | We propose an effective method for inserting adapters into text-to-image
foundation models, which enables the execution of complex downstream tasks
while preserving the generalization ability of the base model. The core idea of
this method is to optimize the attention mechanism related to 2D feature maps,
which enhance... | [
{
"name": "Shengkai Zhang",
"user": "songkey",
"fullname": "Shengkai Zhang",
"avatar": "/avatars/a3d7dee74a73bc56945ac19e8ddcaed9.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Nianhong Jiao",
"user": null,
"fullname": null,
"avatar": null,
"status": ... | null | null | null | songkey | Shengkai Zhang | /avatars/a3d7dee74a73bc56945ac19e8ddcaed9.svg | 622 | 2024-10-30T11:00:51.000Z | true | |
2406.06469 | 2024-06-11 | Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning | [
"Joongwon Kim",
"Bhargavi Paranjape",
"Tushar Khot",
"Hannaneh Hajishirzi"
] | https://github.com/agent-husky/husky-v1 | null | 26 | 2 | 30 | 2024-06-11 | 11 | 15 | 18 | 21 | 4 | 21 | true | 2024-W24 | 2024-06 | false | 2 | 14 | 27 | 90 | 92 | 346 | Language agents perform complex tasks by using tools to execute each step
precisely. However, most existing agents are based on proprietary models or
designed to target specific tasks, such as mathematics or multi-hop question
answering. We introduce Husky, a holistic, open-source language agent that
learns to reason o... | [
{
"name": "Joongwon Kim",
"user": "jwonkim",
"fullname": "Joongwon Kim",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64b81bc20d8834cb3225bbc0/F2ciNosMyIlC2ZLlVTpw2.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Bhargavi Paranjape",
"user"... | null | null | null | akhaliq | AK | 349 | 2024-06-10T17:07:25.000Z | false | ||
2410.11843 | 2024-10-17 | From Commands to Prompts: LLM-based Semantic File System for AIOS | [
"Zeru Shi",
"Kai Mei",
"Mingyu Jin",
"Yongye Su",
"Chaoji Zuo",
"Wenyue Hua",
"Wujiang Xu",
"Yujie Ren",
"Zirui Liu",
"Mengnan Du",
"Dong Deng",
"Yongfeng Zhang"
] | https://github.com/agiresearch/aios-lsfs | null | 3 | 1 | 3 | 2024-10-18 | null | 0 | 1 | 1 | 0 | 1 | true | 2024-W42 | 2024-10 | false | 23 | 23 | 115 | 117 | 470 | 482 | Large language models (LLMs) have demonstrated significant potential in the
development of intelligent applications and systems such as LLM-based agents
and agent operating systems (AIOS). However, when these applications and
systems interact with the underlying file system, the file system still remains
the traditiona... | [
{
"name": "Zeru Shi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Kai Mei",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Mingyu Jin",
"user": null,
"... | null | null | null | IAMJB | JB D. | 55 | 2024-09-23T08:39:16.000Z | false |
End of preview. Expand in Data Studio
Paper Pulse data
The day-by-day upvote history of every Hugging Face Daily Papers entry since 2024-03-12, updated every day. It powers Paper Pulse (Space).
Built from the past revisions of hysts-bot-data/daily-papers-stats and the paper list in hysts-bot-data/daily-papers, both by @hysts, plus paper details from the public Daily Papers API. Thanks to hysts for keeping that record and for releasing it under CC0 1.0.
Files
| File | Rows | What it holds |
|---|---|---|
series.parquet |
one per paper per day | id (arXiv id), day, upvotes, comments: the count shown on the paper's page that day (last snapshot of the day, UTC) |
papers.parquet |
one per paper | title, Daily Papers date, authors (with Hugging Face accounts when linked), organization, submitter, GitHub repo and stars, abstract (summary), upvotes on day 0/1/3/7, up_close (7 days after the Daily Papers date), peak, purged, and rank within its day, ISO week and month |
purges.parquet |
one per event | days when the Hub removed votes from many papers at once: papers affected (n_drop), votes removed, and whether it was deep |
hourly.parquet |
one per paper per hour | id, ts (UTC), upvotes for the papers featured in the last 10 days, from the hourly snapshots of daily-papers-stats |
age_stats.json |
how papers usually do by age: the distribution of upvotes at the end of day 0..7 after their Daily Papers date, and what papers with a given count at day k ended their first week with (ratios by count bin) | |
meta.json |
last day, number of papers, purge days |
Notes
- Upvotes can go down. People unvote, and on a few days the Hub removed votes from many papers at once (2025-09-12, 2025-12-23, 2026-09-16, 2026-09-18; the cause was not announced). The series keeps the raw value of each day and never corrects it. A day counts as a purge when at least max(250, 2% of papers) dropped.
- Rankings use
up_close, the upvotes 7 days after the Daily Papers date, so a later purge does not rewrite past rankings. Papers younger than 7 days are ranked by their current count, and so are the papers whose Daily Papers date is before the history starts (March 12, 2024), which are flagged withearly. - The source has two collection gaps (13 and 7 days). Days without a snapshot have no row.
- Only papers that were featured on Daily Papers are included (about 18,500), not every paper on the Hub.
License
The series, rankings and purge records are released under CC BY 4.0. The source datasets by @hysts are CC0 1.0. Paper titles and abstracts (title, summary) belong to their authors and are included only to identify each paper; they are not covered by this dataset's license.
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