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Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 70 -
Learning From Mistakes Makes LLM Better Reasoner
Paper • 2310.20689 • Published • 28 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 9 -
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Paper • 2308.00436 • Published • 21
Collections
Discover the best community collections!
Collections including paper arxiv:2310.11511
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RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Paper • 2310.01352 • Published • 7 -
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
Paper • 2310.11511 • Published • 74 -
RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models
Paper • 2308.07922 • Published • 17 -
Retrieval-Generation Synergy Augmented Large Language Models
Paper • 2310.05149 • Published • 1
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JudgeLM: Fine-tuned Large Language Models are Scalable Judges
Paper • 2310.17631 • Published • 32 -
AgentTuning: Enabling Generalized Agent Abilities for LLMs
Paper • 2310.12823 • Published • 35 -
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
Paper • 2303.16634 • Published • 3 -
GPT-4 Doesn't Know It's Wrong: An Analysis of Iterative Prompting for Reasoning Problems
Paper • 2310.12397 • Published • 1
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Detecting Pretraining Data from Large Language Models
Paper • 2310.16789 • Published • 10 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
An Emulator for Fine-Tuning Large Language Models using Small Language Models
Paper • 2310.12962 • Published • 14