Papers by Ken Fukuda
ProMQA: Question Answering Dataset for Multimodal Procedural Activity Understanding (2025.naacl-long)
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Kimihiro Hasegawa, Wiradee Imrattanatrai, Zhi-Qi Cheng, Masaki Asada, Susan Holm, Yuran Wang, Ken Fukuda, Teruko Mitamura
| Challenge: | Existing studies typically provide traditional, but less practical evaluation testbeds for multimodal systems. |
| Approach: | They propose a novel evaluation dataset, ProMQA, to measure the advancement of systems in application-oriented scenarios. |
| Outcome: | The proposed evaluation dataset reveals a significant gap between human and competitive multimodal models. |
Evidential Semantic Entropy for LLM Uncertainty Quantification (2026.eacl-long)
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| Challenge: | Existing methods for quantifying uncertainty in large language models do not account for the effects of the semantics of sampled answers. |
| Approach: | They propose to incorporate the semantics of sampled answers to estimate entropy by incorporating the semantic of sample answers into the estimation methods. |
| Outcome: | The proposed method significantly improves uncertainty quantification performance. |
End-to-End Task-Oriented Dialogue Systems Based on Schema (2023.findings-acl)
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| Challenge: | Existing approaches for task-oriented dialogue systems rely on a unified schema across domains, but we propose a schema-aware model for task oriented dialogues based on 'slots' |
| Approach: | They propose a schema-aware end-to-end neural network model for handling task-oriented dialogues based on a dynamic set of slots within a unified schema. |
| Outcome: | The proposed model performs better on a well-known dataset than baselines on 'schema-guided dialogue' systems. |