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cs.CL2025
Benchmark Profiling: Mechanistic Diagnosis of LLM Benchmarks
Dongjun Kim, Gyuho Shim, Yongchan Chun +3
Large Language Models are commonly judged by their scores on standard benchmarks, yet such scores often overstate real capability since they mask the mix of skills a task actually…
cs.CL2025
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval
Yongchan Chun, Minhyuk Kim, Dongjun Kim +2
Automatic Term Extraction (ATE) identifies domain-specific expressions that are crucial for downstream tasks such as machine translation and information retrieval. Although large l…
cs.SE2025
Enhancing LLM Performance Through Debate: An Empirical Study on Multi-Agent Debate for Coding Tasks
Yong Jin Chun, Qihong Chen, Jiawei Li +1
Large Language Models (LLMs) have advanced autonomous agents' planning and decision-making, yet they struggle with complex tasks requiring diverse expertise and multi-step reasonin…