collaborators

14 papers

cs.CL2026

Learning When to Trust via Selective Context Preference Optimization

Xian Sun, Wei Chow, Yingshuo Wang +4

Language models increasingly condition their answers on external signals, and a single misleading one can turn a correct answer wrong. The obvious remedy, training models to resist…

cs.LG2026

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Xian Sun, Wei Gao, Yingshuo Wang +9

Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support…

cs.CV2026

Watch, Remember, Reason: Human-View Video Understanding with MLLMs

Jiahao Meng, Yue Tan, Qi Xu +12

Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research moves from short clips to long, multimodal, and knowledge-intensive video…

cs.AI2026

AI for Auto-Research: Roadmap & User Guide

Lingdong Kong, Xian Sun, Wei Chow +17

AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents can execute experiments, draf…

cs.CV2026

Open-o3-Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence

Jiahao Meng, Xiangtai Li, Haochen Wang +8

Most video reasoning models only generate textual reasoning traces without indicating when and where key evidence appears. Recent models such as OpenAI-o3 have sparked wide interes…

cs.CV2026

ReasonMap: Towards Fine-Grained Visual Reasoning from Transit Maps

Sicheng Feng, Song Wang, Shuyi Ouyang +5

Multimodal large language models (MLLMs) have demonstrated significant progress in semantic scene understanding and text-image alignment, with reasoning variants enhancing performa…