-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 118 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 111 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 122
Collections
Discover the best community collections!
Collections including paper arxiv:2504.16084
-
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 122 -
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 104 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 73
-
Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models
Paper • 2502.04404 • Published • 24 -
Learning Adaptive Parallel Reasoning with Language Models
Paper • 2504.15466 • Published • 38 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 83 -
THOUGHTTERMINATOR: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models
Paper • 2504.13367 • Published • 24
-
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs
Paper • 2501.18585 • Published • 61 -
RWKV-7 "Goose" with Expressive Dynamic State Evolution
Paper • 2503.14456 • Published • 146 -
DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learning
Paper • 2503.15265 • Published • 47 -
Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning
Paper • 2503.15558 • Published • 46
-
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 120 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 70 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 61 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 151
-
Scaling LLM Inference with Optimized Sample Compute Allocation
Paper • 2410.22480 • Published -
Test-time Computing: from System-1 Thinking to System-2 Thinking
Paper • 2501.02497 • Published • 46 -
Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
Paper • 2412.14135 • Published -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 98
-
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 40 -
Token-Budget-Aware LLM Reasoning
Paper • 2412.18547 • Published • 47 -
Efficiently Serving LLM Reasoning Programs with Certaindex
Paper • 2412.20993 • Published • 38 -
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Paper • 2412.17256 • Published • 48
-
How to Synthesize Text Data without Model Collapse?
Paper • 2412.14689 • Published • 53 -
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
Paper • 2412.12094 • Published • 11 -
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
Paper • 2306.07691 • Published • 8 -
iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier Transform
Paper • 2203.02395 • Published
-
LLMs + Persona-Plug = Personalized LLMs
Paper • 2409.11901 • Published • 34 -
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Paper • 2409.12183 • Published • 39 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13 -
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Paper • 2410.00531 • Published • 33