Papers by Jaeyeon Kim
WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations (2026.findings-acl)
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| Challenge: | Large audio-language models extend language understanding into the auditory domain, yet their ability to perform low-level listening, such as pitch and duration detection, remains underexplored. |
| Approach: | They propose a global benchmark to evaluate low-level auditory perception and cognition using marine mammal vocalizations to better assess models’ low- level listening. |
| Outcome: | The proposed models show performance far below human levels, indicating a need for stronger auditory grounding in LALMs. |
Data Descriptions from Large Language Models with Influence Estimation (2025.emnlp-main)
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| Challenge: | Existing explainable AI approaches focus on interpreting how models make predictions. |
| Approach: | They propose a pipeline that generates textual descriptions using large language models . they propose 'cross-modal transfer classification' task to examine effectiveness of textual description . |
| Outcome: | The proposed method improves classification accuracy compared to baselines and sheds light on how the model prioritizes and utilizes information for decision-making. |
Sound of Story: Multi-modal Storytelling with Audio (2023.findings-emnlp)
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| Challenge: | Existing studies on storytelling with sound have focused on visuals and sounds, but little attention has been given to sound. |
| Approach: | They propose to establish a new component called background sound which is story context-based audio without any linguistic information. |
| Outcome: | The proposed dataset is the largest well-curated dataset for storytelling with sound . it contains 27,354 stories with 19.6 images per story and 984 hours of speech-decoupled audio . |