2 citations · 5 across the 14 of their papers we have counts for
7 papers · 1 filter
When Models Hear What They Expect: Diagnosing Prosodic Heuristics in Multimodal Sarcasm Detection
Yongjian Chen, Pengfei Wei, Yiqun Sun +2
Multimodal Large Language Models (MLLMs) process speech and text jointly, yet whether they exploit prosodic cues for pragmatic inference or rely on surface acoustic patterns has re…
GGSS: Geodesic-Gated Spherical Steering for Inference-Time Debiasing of Generative Vision-Language Models
Yiqun Sun, Junyu Chen, Pengfei Wei +1
Generative vision-language models (VLMs) are increasingly used in human-centered settings, yet they can produce demographically biased outputs even when images differ only in contr…
DeepConnect: A Visual Analytics System for Bridging Interdisciplinary Research Collaborations
Yingchaojie Feng, Zekai Shao, Yiqun Sun +2
Interdisciplinary research collaboration is crucial for scientific innovation, but it remains difficult to initiate in practice. Existing collaborator discovery approaches are ofte…
Return of Frustratingly Easy Unsupervised Video Domain Adaptation
Pengfei Wei, Yiqun Sun, Zhiqiang Xu +2
Unsupervised video domain adaptation (UVDA) is a practical but under-explored problem. In this paper, we propose a frustratingly easy UVDA method, called MetaTrans. Specifically, M…
Very Efficient Listwise Multimodal Reranking for Long Documents
Yiqun Sun, Pengfei Wei, Lawrence B. Hsieh
Listwise reranking is a key yet computationally expensive component in vision-centric retrieval and multimodal retrieval-augmented generation (M-RAG) over long documents. While rec…
Corpus2Skill: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG
Yiqun Sun, Pengfei Wei, Lawrence B. Hsieh
Retrieval-Augmented Generation (RAG) grounds LLM responses in external evidence but treats the model as a passive consumer of search results, with no view of how the corpus is orga…
OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agents
Yichao Feng, Haoran Luo, Zhenghong Lin +4
Multi-agent large language model frameworks are promising for complex multi step reasoning, yet existing systems remain weak for scientific and knowledge intensive domains due to s…