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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 141 -
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 • 64
Collections
Discover the best community collections!
Collections including paper arxiv:2310.13127
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Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model
Paper • 2212.09146 • Published • 3 -
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models
Paper • 2308.10633 • Published • 1 -
MemeCap: A Dataset for Captioning and Interpreting Memes
Paper • 2305.13703 • Published -
Contrastive Learning for Inference in Dialogue
Paper • 2310.12467 • Published
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
Tuna: Instruction Tuning using Feedback from Large Language Models
Paper • 2310.13385 • Published • 10 -
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning
Paper • 2310.00492 • Published • 1
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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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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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Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
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 -
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI
Paper • 2401.14019 • Published • 19
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Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 75 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 40 -
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor
Paper • 2212.09689 • Published • 1
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MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 22 -
Neurons in Large Language Models: Dead, N-gram, Positional
Paper • 2309.04827 • Published • 16 -
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Paper • 2309.05516 • Published • 9 -
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs
Paper • 2309.03907 • Published • 8