Qingfa Xiao — accepted AI-conference papers

2026

Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?

Jiaqi Tang, Jianmin Chen, Youyang Zhai, Wei Wei, Runtao Liu, Mengjie Zhao +3

ICML 2026poster

Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in visual understanding, yet their performance degrades significantly under real-world visual corruptions. While existing robustness enhancement approaches exist, they are limited: black-box feature alignment lacks interpr…

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2023

Topic-DPR: Topic-based Prompts for Dense Passage Retrieval

Qingfa Xiao, Shuangyin Li, Lei Chen

EMNLP 2023long findings

Prompt-based learning's efficacy across numerous natural language processing tasks has led to its integration into dense passage retrieval. Prior research has mainly focused on enhancing the semantic understanding of pre-trained language models by optimizing a single vector as a continuous prompt. T…

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