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Collections including paper arxiv:2401.08967
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Instruction Tuning for Large Language Models: A Survey
Paper • 2308.10792 • Published • 1 -
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Paper • 2403.14608 • Published -
Efficient Large Language Models: A Survey
Paper • 2312.03863 • Published • 3 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 30
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Let's Verify Step by Step
Paper • 2305.20050 • Published • 10 -
LLM Critics Help Catch LLM Bugs
Paper • 2407.00215 • Published -
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Paper • 2407.21787 • Published • 12 -
Generative Verifiers: Reward Modeling as Next-Token Prediction
Paper • 2408.15240 • Published • 13
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 8 -
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Paper • 2401.06066 • Published • 45 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 14 -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 28
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PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 53 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 39 -
Context-Aware Meta-Learning
Paper • 2310.10971 • Published • 16
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Large Language Model Alignment: A Survey
Paper • 2309.15025 • Published • 2 -
Aligning Large Language Models with Human: A Survey
Paper • 2307.12966 • Published • 1 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 52 -
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Paper • 2310.05344 • Published • 1
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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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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 17 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 30 -
The Impact of Reasoning Step Length on Large Language Models
Paper • 2401.04925 • Published • 16
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MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 53 -
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Paper • 2401.10774 • Published • 54 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
Paper • 2401.12954 • Published • 29
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 53 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 19 -
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