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cs.CL2025
AutoLogi: Automated Generation of Logic Puzzles for Evaluating Reasoning Abilities of Large Language Models
Qin Zhu, Fei Huang, Runyu Peng +6
While logical reasoning evaluation of Large Language Models (LLMs) has attracted significant attention, existing benchmarks predominantly rely on multiple-choice formats that are v…
cs.CL2024★ 1 cited
Inference-Time Decontamination: Reusing Leaked Benchmarks for Large Language Model Evaluation
Qin Zhu, Qingyuan Cheng, Runyu Peng +5
The training process of large language models (LLMs) often involves varying degrees of test data contamination. Although current LLMs are achieving increasingly better performance…
cs.CL2024★ 2 cited
Unified Active Retrieval for Retrieval Augmented Generation
Qinyuan Cheng, Xiaonan Li, Shimin Li +7
In Retrieval-Augmented Generation (RAG), retrieval is not always helpful and applying it to every instruction is sub-optimal. Therefore, determining whether to retrieve is crucial…