activity
20222025
most citedQwen3-VL Technical Report

16 citations · 21 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CV202516 cited

Qwen3-VL Technical Report

Shuai Bai, Yuxuan Cai, Ruizhe Chen +61

We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…

cs.CV2025

Beyond Isolated Facts: Synthesizing Narrative and Grounded Supervision for VideoQA

Jianxin Liang, Tan Yue, Yuxuan Wang +4

The performance of Video Question Answering (VideoQA) models is fundamentally constrained by the nature of their supervision, which typically consists of isolated, factual question…

cs.CL20252 cited

Qwen3-Omni Technical Report

Jin Xu, Zhifang Guo, Hangrui Hu +35

We present Qwen3-Omni, a single multimodal model that, for the first time, maintains state-of-the-art performance across text, image, audio, and video without any degradation relat…

cs.CV20252 cited

SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence

Zhitao Zeng, Zhu Zhuo, Xiaojun Jia +12

Foundation models have achieved transformative success across biomedical domains by enabling holistic understanding of multimodal data. However, their application in surgery remain…

cs.LG2025

Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space

Hengli Li, Chenxi Li, Tong Wu +8

Reasoning ability, a core component of human intelligence, continues to pose a significant challenge for Large Language Models (LLMs) in the pursuit of AGI. Although model performa…

cs.CV2025

Probing and Inducing Combinational Creativity in Vision-Language Models

Yongqian Peng, Yuxi Ma, Mengmeng Wang +5

The ability to combine existing concepts into novel ideas stands as a fundamental hallmark of human intelligence. Recent advances in Vision-Language Models (VLMs) like GPT-4V and D…