activity
20242026
most citedSNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection

4 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Chatbot Engagement Does Not Always Beget Metalearning: Evidence from Three Countries

Kokil Jaidka, Insyirah Binte Imam Mujtahid, Peng Qi +5

Chatbots deliver real-time fact-checks, but whether a chatbot correction leaves anything behind once the chatbot is gone - metalearning, distinct from correcting misbeliefs - is un…

cs.IR2026

Subtraction Gets You More: Gap-Aware Retrieval for Multimodal Multi-Hop QA

Sunah O, Jay-Yoon Lee

In multimodal multi-hop question answering, we focus on the initial retrieval stage via two distinct tasks: (1) evidence set completion, retrieving missing evidence given context,…

cs.CV2025

TRUST-VL: An Explainable News Assistant for General Multimodal Misinformation Detection

Zehong Yan, Peng Qi, Wynne Hsu +1

Multimodal misinformation, encompassing textual, visual, and cross-modal distortions, poses an increasing societal threat that is amplified by generative AI. Existing methods typic…

cs.MM2025★ 1 cited

Mitigating GenAI-Powered Evidence Pollution for Out-Of-Context Misinformation Detection

Zehong Yan, Peng Qi, Wynne Hsu +1

While generative artificial intelligence (GenAI) models have achieved significant success, their misuse for generating deceptive content raises growing concerns about online inform…

cs.MM2024★ 4 cited

SNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection

Peng Qi, Zehong Yan, Wynne Hsu +1

Misinformation is a prevalent societal issue due to its potential high risks. Out-of-context (OOC) misinformation, where authentic images are repurposed with false text, is one of…