activity
20242026
most citedVideoPrism: A Foundational Visual Encoder for Video Understanding

14 citations · 15 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection

Siheng Wang, Yanshu Li, Bohan Hu +12

Open-vocabulary object detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in practical deployment. On the one…

cs.CL2026

MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts

Weiyue Li, Ruizhi Qian, Yi Li +5

Large language models (LLMs) are widely explored for reasoning-intensive research tasks, yet resources for testing whether they can infer scientific conclusions from structured bio…

cs.CL2026

TrailBlazer: History-Guided Reinforcement Learning for Black-Box LLM Jailbreaking

Sung-Hoon Yoon, Ruizhi Qian, Minda Zhao +2

Large Language Models (LLMs) have become integral to many domains, making their safety a critical priority. Prior jailbreaking research has explored diverse approaches, including p…

cs.LG2025★ 1 cited

LLM-Powered Text-Attributed Graph Anomaly Detection via Retrieval-Augmented Reasoning

Haoyan Xu, Ruizhi Qian, Zhengtao Yao +10

Anomaly detection on attributed graphs plays an essential role in applications such as fraud detection, intrusion monitoring, and misinformation analysis. However, text-attributed…

cs.LG2025

A Systematic Study of Model Extraction Attacks on Graph Foundation Models

Haoyan Xu, Ruizhi Qian, Jiate Li +9

Graph machine learning has advanced rapidly in tasks such as link prediction, anomaly detection, and node classification. As models scale up, pretrained graph models have become va…

cs.CV2025

CogStream: Context-guided Streaming Video Question Answering

Zicheng Zhao, Kangyu Wang, Shijie Li +3

Despite advancements in Video Large Language Models (Vid-LLMs) improving multimodal understanding, challenges persist in streaming video reasoning due to its reliance on contextual…