Papers by Jiyun Chun
Beyond Length: Context-Aware Expansion and Independence as Developmentally Sensitive Evaluation in Child Utterances (2026.eacl-long)
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| Challenge: | Common proxies such as Mean Length of Utterance (MLU), lexical diversity (vocd-D), and readability indices are dominated by length and ignore conversational context, missing aspects of response quality such as reasoning depth, topic maintenance, and discourse planning. |
| Approach: | They propose a framework that classifies the Previous Adult Utterance Type and scores the child’s response along two axes: Expansion (contextual elaboration and inferential depth) and Independence (the child’ s contribution to advancing the discourse). |
| Outcome: | The proposed framework assesses the child's response along two axes: Expansion (contextual elaboration and inferential depth) and Independence (the child’s contribution to advancing the discourse). |
Do Audio LLMs Really LISTEN, or Just Transcribe? Measuring Lexical vs. Acoustic Emotion Cues Reliance (2026.eacl-long)
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| Challenge: | LISTEN is a controlled benchmark to disentangle lexical reliance from acoustic sensitivity in emotion understanding. |
| Approach: | They propose a benchmark to disentangle lexical reliance from acoustic sensitivity in emotion understanding. |
| Outcome: | LISTEN shows that current LALMs largely "transcribe" rather than "listen" authors note that models underutilize acoustic cues while relying on lexical semantics . |
ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback (2024.emnlp-main)
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| Challenge: | Large Multimodal Models excel at comprehending human instructions and demonstrate remarkable results across a broad spectrum of tasks. |
| Approach: | They propose an algorithm that alters REinforcement Learning and Supervised Fine-Tuning to refine large multimodal models with specific preferences. |
| Outcome: | The proposed algorithm achieves 70% win rate compared to baseline models judged by GPT-4o. |