Papers by Esther Gan
ComicVQA: A Benchmark for Visual Reasoning in Multimodal LLMs (2026.findings-acl)
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| Challenge: | ComicVQA is a visual reasoning benchmark for comics. |
| Approach: | They propose a comics-based benchmark for evaluating MLLMs on visual reasoning. |
| Outcome: | The proposed model achieves 62.6% accuracy on Missing Panel Prediction and 46.4% on Panel Sorting, compared to open-source models. |
Reasoning Robustness of LLMs to Adversarial Typographical Errors (2024.emnlp-main)
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Esther Gan, Yiran Zhao, Liying Cheng, Mao Yancan, Anirudh Goyal, Kenji Kawaguchi, Min-Yen Kan, Michael Shieh
| Challenge: | Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning using Chain-of-Thought (CoT) prompting. |
| Approach: | They develop an algorithm that iteratively samples typos for words that are important to the query and selects the edit that is most likely to succeed in attacking. |
| Outcome: | The proposed algorithm detects typographical errors in large and closed-source LLMs and shows that they are robust to them. |