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Collections including paper arxiv:2310.01352

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

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval

Paper • 2310.15511 • Published Oct 24, 2023 • 4
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search

Paper • 2310.13227 • Published Oct 20, 2023 • 13
Reverse Chain: A Generic-Rule for LLMs to Master Multi-API Planning

Paper • 2310.04474 • Published Oct 6, 2023 • 2
AgentTuning: Enabling Generalized Agent Abilities for LLMs

Paper • 2310.12823 • Published Oct 19, 2023 • 35

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Paper • 2310.11511 • Published Oct 17, 2023 • 75
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models

Paper • 2308.10633 • Published Aug 21, 2023 • 1
RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Paper • 2310.01352 • Published Oct 2, 2023 • 7
RAGAS: Automated Evaluation of Retrieval Augmented Generation

Paper • 2309.15217 • Published Sep 26, 2023 • 3

WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia

Paper • 2305.14292 • Published May 23, 2023 • 1
Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps

Paper • 2312.07796 • Published Dec 12, 2023
RAGAS: Automated Evaluation of Retrieval Augmented Generation

Paper • 2309.15217 • Published Sep 26, 2023 • 3
Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering

Paper • 2210.02627 • Published Oct 6, 2022

RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Paper • 2310.01352 • Published Oct 2, 2023 • 7
Self-Consistency Improves Chain of Thought Reasoning in Language Models

Paper • 2203.11171 • Published Mar 21, 2022 • 3
MemGPT: Towards LLMs as Operating Systems

Paper • 2310.08560 • Published Oct 12, 2023 • 7
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Paper • 2310.06117 • Published Oct 9, 2023 • 3

RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Paper • 2310.01352 • Published Oct 2, 2023 • 7
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Paper • 2310.11511 • Published Oct 17, 2023 • 75
RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

Paper • 2308.07922 • Published Aug 15, 2023 • 17
Retrieval-Generation Synergy Augmented Large Language Models

Paper • 2310.05149 • Published Oct 8, 2023 • 1

JudgeLM: Fine-tuned Large Language Models are Scalable Judges

Paper • 2310.17631 • Published Oct 26, 2023 • 33
AgentTuning: Enabling Generalized Agent Abilities for LLMs

Paper • 2310.12823 • Published Oct 19, 2023 • 35
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Paper • 2303.16634 • Published Mar 29, 2023 • 3
GPT-4 Doesn't Know It's Wrong: An Analysis of Iterative Prompting for Reasoning Problems

Paper • 2310.12397 • Published Oct 19, 2023 • 1

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