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Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 19 -
Evaluating Very Long-Term Conversational Memory of LLM Agents
Paper • 2402.17753 • Published • 18 -
Resonance RoPE: Improving Context Length Generalization of Large Language Models
Paper • 2403.00071 • Published • 23 -
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences
Paper • 2403.09347 • Published • 20
Collections
Discover the best community collections!
Collections including paper arxiv:2402.10171
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LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 115 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 24 -
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Paper • 2402.11550 • Published • 16 -
The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey
Paper • 2401.07872 • Published • 2
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In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss
Paper • 2402.10790 • Published • 41 -
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Paper • 2402.11550 • Published • 16 -
A Neural Conversational Model
Paper • 1506.05869 • Published • 2 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 24
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 105 -
How to Train Data-Efficient LLMs
Paper • 2402.09668 • Published • 41 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 20 -
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
Paper • 2402.09727 • Published • 37
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PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
Paper • 2402.08714 • Published • 12 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 24 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 10 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 13
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Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon
Paper • 2401.03462 • Published • 27 -
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
Paper • 2305.07185 • Published • 9 -
YaRN: Efficient Context Window Extension of Large Language Models
Paper • 2309.00071 • Published • 66 -
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache
Paper • 2401.02669 • Published • 14
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Ziya2: Data-centric Learning is All LLMs Need
Paper • 2311.03301 • Published • 16 -
Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 16 -
TinyGSM: achieving >80% on GSM8k with small language models
Paper • 2312.09241 • Published • 37 -
Time is Encoded in the Weights of Finetuned Language Models
Paper • 2312.13401 • Published • 20
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CLEX: Continuous Length Extrapolation for Large Language Models
Paper • 2310.16450 • Published • 9 -
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models
Paper • 2401.06951 • Published • 25 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 24
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LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 88 -
LMDX: Language Model-based Document Information Extraction and Localization
Paper • 2309.10952 • Published • 65 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 39 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 96
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FLM-101B: An Open LLM and How to Train It with $100K Budget
Paper • 2309.03852 • Published • 44 -
Extending LLMs' Context Window with 100 Samples
Paper • 2401.07004 • Published • 15 -
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Paper • 2402.11550 • Published • 16 -
The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey
Paper • 2401.07872 • Published • 2