Papers by Takayuki Okatani
CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning (2026.eacl-long)
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| Challenge: | Existing datasets for multimodal table understanding provide short factual answers without explicit multi-step reasoning supervision. |
| Approach: | They propose a code-driven reasoning framework that produces scalable, interpretable, and automatically verifiable annotations by coupling multi-step reasoning with executable Python code. |
| Outcome: | The proposed model achieves significant gains over baseline models while producing transparent and verifiable reasoning traces. |