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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 144 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 12 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 51 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 45
Collections
Discover the best community collections!
Collections including paper arxiv:2402.13753
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Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 38 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 82 -
Language Modeling Is Compression
Paper • 2309.10668 • Published • 82
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Self-Play Preference Optimization for Language Model Alignment
Paper • 2405.00675 • Published • 24 -
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 11 -
Attention Is All You Need
Paper • 1706.03762 • Published • 44 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Paper • 2307.08691 • Published • 8
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LLoCO: Learning Long Contexts Offline
Paper • 2404.07979 • Published • 20 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111 -
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Paper • 2402.11550 • Published • 15 -
LongAlign: A Recipe for Long Context Alignment of Large Language Models
Paper • 2401.18058 • Published • 21
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 96 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 104 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 43
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Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 104 -
sDPO: Don't Use Your Data All at Once
Paper • 2403.19270 • Published • 40 -
ViTAR: Vision Transformer with Any Resolution
Paper • 2403.18361 • Published • 52 -
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Paper • 2403.18814 • Published • 44
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Sequence Parallelism: Long Sequence Training from System Perspective
Paper • 2105.13120 • Published • 5 -
Ring Attention with Blockwise Transformers for Near-Infinite Context
Paper • 2310.01889 • Published • 10 -
Striped Attention: Faster Ring Attention for Causal Transformers
Paper • 2311.09431 • Published • 4 -
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models
Paper • 2309.14509 • Published • 17
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GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 182 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 67 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 62 -
InternLM2 Technical Report
Paper • 2403.17297 • Published • 29
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AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 11 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT
Paper • 2402.16840 • Published • 23 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111