papers

Publications (12)

cs.CV2026

Reasoning Resides in Layers: Restoring Temporal Reasoning in Video-Language Models with Layer-Selective Merging

Zihang Fu, Haonan Wang, Jian Kang +2

Multimodal adaptation equips large language models (LLMs) with perceptual capabilities, but often weakens the reasoning ability inherited from language-only pretraining. This trade…

cs.CL2021

Don't Change Me! User-Controllable Selective Paraphrase Generation

Mohan Zhang, Luchen Tan, Zhengkai Tu +4

In the paraphrase generation task, source sentences often contain phrases that should not be altered. Which phrases, however, can be context dependent and can vary by application.…

cs.CL2025

TaleFrame: An Interactive Story Generation System with Fine-Grained Control and Large Language Models

Yunchao Wang, Guodao Sun, Zihang Fu +4

With the advancement of natural language generation (NLG) technologies, creative story generation systems have gained increasing attention. However, current systems often fail to a…

cs.CL2026

Better with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notes

Zihang Fu, Fanxiao Li, Jianyang Gu +5

Large Language Model (LLM)-augmented Community Notes offer a scalable path for timely, evidence-grounded correction of health misinformation on social platforms. However, they stil…

cs.CV2026

InfoAffect: Affective Annotations of Infographics in Information Spread

Zihang Fu, Yunchao Wang, Chenyu Huang +2

Infographics are widely used in social media to convey complex information, yet how they influence users' affects remains underexplored due to the scarcity of relevant datasets. To…

cs.SI2026

Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation

Jiaying Wu, Zihang Fu, Haonan Wang +4

Community Notes, the crowd-sourced misinformation governance system on X (formerly Twitter), allows users to flag misleading posts, attach contextual notes, and rate the notes' hel…

cs.LG2025

Personalized Interpolation: Achieving Efficient Conversion Estimation with Flexible Optimization Windows

Xin Zhang, Weiliang Li, Rui Li +9

Optimizing conversions is crucial in modern online advertising systems, enabling advertisers to deliver relevant products to users and drive business outcomes. However, accurately…

cs.HC2025

Human-Computer Interaction and Visualization in Natural Language Generation Models: Applications, Challenges, and Opportunities

Yunchao Wang, Guodao Sun, Zihang Fu +1

Natural language generation (NLG) models have emerged as a focal point of research within natural language processing (NLP), exhibiting remarkable performance in tasks such as text…

cs.CL2025

From Harm to Help: Turning Reasoning In-Context Demos into Assets for Reasoning LMs

Haonan Wang, Weida Liang, Zihang Fu +8

Recent reasoning LLMs (RLMs), especially those trained with verifier-based reinforcement learning, often perform worse with few-shot CoT than with direct answering. We revisit this…

cs.CL2020

Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documents

Ruixue Zhang, Wei Yang, Luyun Lin +7

Techniques for automatically extracting important content elements from business documents such as contracts, statements, and filings have the potential to make business operations…

cs.LG2026

MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction

Shiwen Shen, Xiru Huang, Liang Luo +32

Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), yet treats every click as the…

cs.CV2026

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…