Papers by Peng Chuang
QaDialMoE: Question-answering Dialogue based Fact Verification with Mixture of Experts (2022.findings-emnlp)
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| Challenge: | Existing research on fact verification focuses on news, tables and Wikipedia passages. |
| Approach: | They propose a question-answering dialogue based fact verification with mixture of experts that exploits questions and evidence effectively in the verification process. |
| Outcome: | The proposed approach outperforms previous approaches on three benchmark datasets and achieves state-of-the-art results. |
From Imitation to Discrimination: Progressive Curriculum Learning for Robust Web Navigation (2026.findings-acl)
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| Challenge: | Text-based web agents offer computational efficiency for autonomous web navigation, yet they lack discrimination capabilities to reject plausible but incorrect elements in densely populated pages. |
| Approach: | They propose a model that uses a text-based web agent to learn to discriminate against incorrect elements in densely populated HTML and a training curriculum to synthesize diverse cross-domain tasks with strict verification. |
| Outcome: | Empirical evaluation shows that the model performs better than open-source models with 58.7% step success rate. |