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LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 21 -
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Paper • 2402.11550 • Published • 15 -
The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey
Paper • 2401.07872 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2310.10638
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Detecting Pretraining Data from Large Language Models
Paper • 2310.16789 • Published • 10 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
An Emulator for Fine-Tuning Large Language Models using Small Language Models
Paper • 2310.12962 • Published • 14
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CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization
Paper • 2310.10134 • Published • 1 -
TiC-CLIP: Continual Training of CLIP Models
Paper • 2310.16226 • Published • 8 -
In-Context Pretraining: Language Modeling Beyond Document Boundaries
Paper • 2310.10638 • Published • 28 -
Controlled Decoding from Language Models
Paper • 2310.17022 • Published • 14
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Ada-Instruct: Adapting Instruction Generators for Complex Reasoning
Paper • 2310.04484 • Published • 5 -
Diversity of Thought Improves Reasoning Abilities of Large Language Models
Paper • 2310.07088 • Published • 5 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Paper • 2310.13332 • Published • 14
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper • 2202.07922 • Published • 1 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4
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TRAMS: Training-free Memory Selection for Long-range Language Modeling
Paper • 2310.15494 • Published • 1 -
A Long Way to Go: Investigating Length Correlations in RLHF
Paper • 2310.03716 • Published • 9 -
YaRN: Efficient Context Window Extension of Large Language Models
Paper • 2309.00071 • Published • 65 -
Giraffe: Adventures in Expanding Context Lengths in LLMs
Paper • 2308.10882 • Published • 1
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KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Paper • 2310.15511 • Published • 4 -
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
Paper • 2310.13227 • Published • 12 -
Reverse Chain: A Generic-Rule for LLMs to Master Multi-API Planning
Paper • 2310.04474 • Published • 2 -
AgentTuning: Enabling Generalized Agent Abilities for LLMs
Paper • 2310.12823 • Published • 35
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Dissecting In-Context Learning of Translations in GPTs
Paper • 2310.15987 • Published • 5 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 41 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper • 2202.07922 • Published • 1 -
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques
Paper • 2310.08101 • Published • 1
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BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 96 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 74 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 41 -
Matryoshka Diffusion Models
Paper • 2310.15111 • Published • 40
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In-Context Pretraining: Language Modeling Beyond Document Boundaries
Paper • 2310.10638 • Published • 28 -
Magicoder: Source Code Is All You Need
Paper • 2312.02120 • Published • 79 -
Parameter Efficient Tuning Allows Scalable Personalization of LLMs for Text Entry: A Case Study on Abbreviation Expansion
Paper • 2312.14327 • Published • 6 -
WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation
Paper • 2312.14187 • Published • 49