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Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 47 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 21 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 609
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Collections including paper arxiv:2402.17764
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BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 49 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 19
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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 • 53 -
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Paper • 2310.05344 • Published • 1
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Distributed Inference and Fine-tuning of Large Language Models Over The Internet
Paper • 2312.08361 • Published • 28 -
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 31 -
Efficient Memory Management for Large Language Model Serving with PagedAttention
Paper • 2309.06180 • Published • 25 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 609
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DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 26 -
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Paper • 2402.14905 • Published • 127 -
Resonance RoPE: Improving Context Length Generalization of Large Language Models
Paper • 2403.00071 • Published • 23 -
AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 13
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OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Paper • 2402.01739 • Published • 27 -
Rethinking Interpretability in the Era of Large Language Models
Paper • 2402.01761 • Published • 23 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 115 -
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Paper • 2402.07827 • Published • 47
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Paper • 2402.05140 • Published • 22 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 49 -
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Paper • 2402.14658 • Published • 82