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Rethinking Optimization and Architecture for Tiny Language Models
Paper • 2402.02791 • Published • 12 -
More Agents Is All You Need
Paper • 2402.05120 • Published • 51 -
Scaling Laws for Forgetting When Fine-Tuning Large Language Models
Paper • 2401.05605 • Published -
Aligning Large Language Models with Counterfactual DPO
Paper • 2401.09566 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2402.10193
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18 -
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
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 27 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 20 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 63
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LLaMA Pro: Progressive LLaMA with Block Expansion
Paper • 2401.02415 • Published • 53 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 94 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 17 -
Generative Representational Instruction Tuning
Paper • 2402.09906 • Published • 51
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Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 27 -
Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models
Paper • 2311.08692 • Published • 12 -
Exponentially Faster Language Modelling
Paper • 2311.10770 • Published • 117 -
Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 16
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PockEngine: Sparse and Efficient Fine-tuning in a Pocket
Paper • 2310.17752 • Published • 11 -
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 28 -
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Paper • 2311.06243 • Published • 17 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 28
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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 22 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Paper • 2309.16119 • Published • 1 -
LoRA ensembles for large language model fine-tuning
Paper • 2310.00035 • Published • 2
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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 22 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models
Paper • 2309.02784 • Published • 1 -
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Paper • 2309.16119 • Published • 1
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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 • 75 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 79 -
Language Modeling Is Compression
Paper • 2309.10668 • Published • 82