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Collections including paper arxiv:2310.13127

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 140
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17 • 27
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16 • 20
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 63

Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model

Paper • 2212.09146 • Published Dec 18, 2022 • 3
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models

Paper • 2308.10633 • Published Aug 21, 2023 • 1
MemeCap: A Dataset for Captioning and Interpreting Memes

Paper • 2305.13703 • Published May 23, 2023
Contrastive Learning for Inference in Dialogue

Paper • 2310.12467 • Published Oct 19, 2023

Papers: Instruct

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning

Paper • 2310.00492 • Published Sep 30, 2023 • 1

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 18
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

Research Papers

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI

Paper • 2401.14019 • Published Jan 25 • 19

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11

LLM Instructions

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Paper • 2310.13127 • Published Oct 19, 2023 • 11
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

Data enrichment methods for pre-training and fine-tuning

Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 75
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Paper • 2309.00267 • Published Sep 1, 2023 • 47
Self-Alignment with Instruction Backtranslation

Paper • 2308.06259 • Published Aug 11, 2023 • 40
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Paper • 2212.09689 • Published Dec 19, 2022 • 1

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Paper • 2309.04662 • Published Sep 9, 2023 • 22
Neurons in Large Language Models: Dead, N-gram, Positional

Paper • 2309.04827 • Published Sep 9, 2023 • 16
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

Paper • 2309.05516 • Published Sep 11, 2023 • 9
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

Paper • 2309.03907 • Published May 18, 2023 • 8

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