Papers by Kuei-Chun Kao
QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models (2025.emnlp-main)
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| Challenge: | Existing prompting methods for multimodal large language models lack fine-grained perception across disparate images . existing methods fail to integrate perception and reasoning, causing problems with general multi-image reasoning tasks. |
| Approach: | They propose a generalized prompting method that integrates perception and reasoning . they evaluate the method on open-source and closed-source MLLMs . |
| Outcome: | The proposed method shows competitive performance across tasks and improves in challenging scenarios. |
Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? (2024.findings-emnlp)
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| Challenge: | Existing benchmarks for Large Language Models often feature simple problems with only one or two unknown variables, which do not sufficiently challenge their reasoning capacities. |
| Approach: | They propose a new benchmark, BeyondX, which progressively increases complexity by expanding the number of unknowns in simpler problems. |
| Outcome: | The proposed approach improves performance on the BeyondX benchmark and provides deeper insights into the computational limits of LLMs when faced with more complex mathematical challenges. |