Papers by Peng Chuang

2 papers
QaDialMoE: Question-answering Dialogue based Fact Verification with Mixture of Experts (2022.findings-emnlp)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations