CritiQ: Mining Data Quality Criteria from Human Preferences

arXiv:2502.19279 · cs.CL · Submitted 2025-02-26 · Read on arXiv

cs.CL

Submitted: 2025-02-26

Updated: 2025-09-11

Comments: to be published in ACL 2025, Code is available at https://github.com/KYLN24/CritiQ

Journal ref: https://aclanthology.org/2025.acl-long.792/

DOI: 10.18653/v1/2025.acl-long.792

Code: https://github.com/KYLN24/CritiQ

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 34× in this paper · explained in 1 episode
• Downstream Tasks — 7× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Perplexity — 4× in this paper · explained in 3 episodes
• Prompt Engineering — 4× in this paper · explained in 4 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Bradley-Terry model — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Modularity — 2× in this paper · explained in 9 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Commentary — 1× in this paper · explained in 2 episodes
• Data Pruning — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Program Synthesis with Large Language Models
• InternLM2 Technical Report
• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
• Evaluating Large Language Models Trained on Code
• DeepSeek-V3 Technical Report
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Training Verifiers to Solve Math Word Problems
• The Llama 3 Herd of Models
• Textbooks Are All You Need
• Measuring Mathematical Problem Solving With the MATH Dataset
• LongWanjuan: Towards Systematic Measurement for Long Text Quality
• OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
• Self-Refine: Iterative Refinement with Self-Feedback
• Large Language Models are Zero-Shot Reasoners
• When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale
• Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
• Pretraining Language Models with Human Preferences
• Decoupled Weight Decay Regularization
• StarCoder 2 and The Stack v2: The Next Generation
• GPT-4 Technical Report

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