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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 • 44 -
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
Collections
Discover the best community collections!
Collections including paper arxiv:2401.00788
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Creative Robot Tool Use with Large Language Models
Paper • 2310.13065 • Published • 8 -
CodeCoT and Beyond: Learning to Program and Test like a Developer
Paper • 2308.08784 • Published • 5 -
Lemur: Harmonizing Natural Language and Code for Language Agents
Paper • 2310.06830 • Published • 30 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 73
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4 -
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
Evaluating the Robustness to Instructions of Large Language Models
Paper • 2308.14306 • Published • 1
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Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts
Paper • 2309.07430 • Published • 27 -
MindAgent: Emergent Gaming Interaction
Paper • 2309.09971 • Published • 11 -
Cure the headache of Transformers via Collinear Constrained Attention
Paper • 2309.08646 • Published • 12 -
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 37