5 papers
The Facade of Truth: Uncovering and Mitigating LLM Susceptibility to Deceptive Evidence
Herun Wan, Jiaying Wu, Minnan Luo +3
To reliably assist human decision-making, LLMs must maintain factual internal beliefs against misleading injections. While current models resist explicit misinformation, we uncover…
What's Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews
Fanxiao Li, Jiaying Wu, Tingchao Fu +4
Even when factually correct, social-media news previews (image-headline pairs) can induce interpretation drift: by selectively omitting crucial context, they lead readers to form j…
Forecasting the Buzz: Enriching Hashtag Popularity Prediction with LLM Reasoning
Yifei Xu, Jiaying Wu, Herun Wan +3
Hashtag trends ignite campaigns, shift public opinion, and steer millions of dollars in advertising spend, yet forecasting which tag goes viral is elusive. Classical regressors dig…
Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models
Jiaying Wu, Fanxiao Li, Zihang Fu +2
The impact of multimodal misinformation arises not only from factual inaccuracies but also from the misleading narratives that creators deliberately embed. Interpreting such creato…
CCSBench: Evaluating Compositional Controllability in LLMs for Scientific Document Summarization
Yixi Ding, Jiaying Wu, Tongyao Zhu +3
To broaden the dissemination of scientific knowledge to diverse audiences, it is desirable for scientific document summarization systems to simultaneously control multiple attribut…