Papers by Youngchae Ahn
P-CoT: A Pedagogically-motivated Participatory Chain-of-Thought Prompting for Phonological Reasoning in LLMs (2025.findings-acl)
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| Challenge: | Using the PhonologyBench benchmark, we assess tasks like rhyme word generation, g2p conversion, and syllable counting. |
| Approach: | They evaluate phonological reasoning in text-based large language models using the PhonologyBench benchmark and a Pedagogically-motivated Participatory Chain-of-Thought prompt. |
| Outcome: | The proposed model achieves up to 52% improvement and surpasses human baselines in certain tasks. |
RCScore: Quantifying Response Consistency in Large Language Models (2025.emnlp-main)
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| Challenge: | Current evaluations of large language models rely on a single instruction template, overlooking models’ sensitivity to instruction style. |
| Approach: | They propose a multi-dimensional framework quantifying how instruction formulation affects model responses by transforming benchmark problems into multiple instruction styles. |
| Outcome: | The proposed framework reveals that instruction style can shift accuracy by 16.7% points. |