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Scaling Instruction-Finetuned Language Models
Paper • 2210.11416 • Published • 7 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 60 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 62
Collections
Discover the best community collections!
Collections including paper arxiv:2402.16107
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Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
Paper • 2403.02677 • Published • 16 -
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Paper • 2403.03003 • Published • 9 -
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
Paper • 2403.01487 • Published • 14 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 44
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MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Paper • 2402.15627 • Published • 34 -
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Paper • 2402.16822 • Published • 15 -
FuseChat: Knowledge Fusion of Chat Models
Paper • 2402.16107 • Published • 36 -
Multi-LoRA Composition for Image Generation
Paper • 2402.16843 • Published • 28
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18 -
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition
Paper • 2402.15220 • Published • 19 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 144 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 28 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 21 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 65
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LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 87 -
NEFTune: Noisy Embeddings Improve Instruction Finetuning
Paper • 2310.05914 • Published • 14 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 56 -
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon
Paper • 2401.03462 • Published • 27
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138 -
SparQ Attention: Bandwidth-Efficient LLM Inference
Paper • 2312.04985 • Published • 38 -
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Paper • 2402.00159 • Published • 59 -
Neural Network Diffusion
Paper • 2402.13144 • Published • 94