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Collections including paper arxiv:2310.13385

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 22
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

Papers: Instruct

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

Paper • 2310.13961 • Published Oct 21, 2023 • 5
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 • 12
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning

Paper • 2310.00492 • Published Sep 30, 2023 • 2

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 37
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

Knowledge distillation

Democratizing Reasoning Ability: Tailored Learning from Large Language Model

Paper • 2310.13332 • Published Oct 20, 2023 • 16
Teaching Language Models to Self-Improve through Interactive Demonstrations

Paper • 2310.13522 • Published Oct 20, 2023 • 12
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection

Paper • 2310.05035 • Published Oct 8, 2023 • 1
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

Dataset generation

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

Paper • 2310.13961 • Published Oct 21, 2023 • 5
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 • 19
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 22
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 69

CLEX: Continuous Length Extrapolation for Large Language Models

Paper • 2310.16450 • Published Oct 25, 2023 • 10
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 • 19
Contrastive Prefence Learning: Learning from Human Feedback without RL

Paper • 2310.13639 • Published Oct 20, 2023 • 25
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

Instruction Dataset

Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca

Paper • 2309.08958 • Published Sep 16, 2023 • 2
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering

Paper • 2309.06358 • Published Sep 3, 2023 • 1
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10
Retrieval-Generation Synergy Augmented Large Language Models

Paper • 2310.05149 • Published Oct 8, 2023 • 1

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

Paper • 2310.13961 • Published Oct 21, 2023 • 5
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 • 12
Evaluating the Robustness to Instructions of Large Language Models

Paper • 2308.14306 • Published Aug 28, 2023 • 1

Moral Foundations of Large Language Models

Paper • 2310.15337 • Published Oct 23, 2023 • 1
Specific versus General Principles for Constitutional AI

Paper • 2310.13798 • Published Oct 20, 2023 • 3
Contrastive Prefence Learning: Learning from Human Feedback without RL

Paper • 2310.13639 • Published Oct 20, 2023 • 25
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Paper • 2309.00267 • Published Sep 1, 2023 • 52

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 42
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 22
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 38

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 22
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 69

Papers: Instruct

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

Paper • 2310.13961 • Published Oct 21, 2023 • 5
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 • 12
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning

Paper • 2310.00492 • Published Sep 30, 2023 • 2

CLEX: Continuous Length Extrapolation for Large Language Models

Paper • 2310.16450 • Published Oct 25, 2023 • 10
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 • 19
Contrastive Prefence Learning: Learning from Human Feedback without RL

Paper • 2310.13639 • Published Oct 20, 2023 • 25
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 37
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

Instruction Dataset

Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca

Paper • 2309.08958 • Published Sep 16, 2023 • 2
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering

Paper • 2309.06358 • Published Sep 3, 2023 • 1
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10
Retrieval-Generation Synergy Augmented Large Language Models

Paper • 2310.05149 • Published Oct 8, 2023 • 1

Knowledge distillation

Democratizing Reasoning Ability: Tailored Learning from Large Language Model

Paper • 2310.13332 • Published Oct 20, 2023 • 16
Teaching Language Models to Self-Improve through Interactive Demonstrations

Paper • 2310.13522 • Published Oct 20, 2023 • 12
Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection

Paper • 2310.05035 • Published Oct 8, 2023 • 1
Tuna: Instruction Tuning using Feedback from Large Language Models

Paper • 2310.13385 • Published Oct 20, 2023 • 10

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

Paper • 2310.13961 • Published Oct 21, 2023 • 5
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 • 12
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 • 5
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 • 19
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

Moral Foundations of Large Language Models

Paper • 2310.15337 • Published Oct 23, 2023 • 1
Specific versus General Principles for Constitutional AI

Paper • 2310.13798 • Published Oct 20, 2023 • 3
Contrastive Prefence Learning: Learning from Human Feedback without RL

Paper • 2310.13639 • Published Oct 20, 2023 • 25
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Paper • 2309.00267 • Published Sep 1, 2023 • 52

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