activity
20242026
most citedQwen3-VL Technical Report

16 citations · 16 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Seg-ReSearch: Segmentation with Interleaved Reasoning and External Search

Tianming Liang, Qirui Du, Jian-Fang Hu +3

Segmentation based on language has been a popular topic in computer vision. While recent advances in multimodal large language models (MLLMs) have endowed segmentation systems with…

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

MCFormer: A Multi-Cost-Volume Network and Comprehensive Benchmark for Particle Image Velocimetry

Zicheng Lin, Xiaoqiang Li, Yichao Wang +1

Particle Image Velocimetry (PIV) is fundamental to fluid dynamics, yet deep learning applications face significant hurdles. A critical gap exists: the lack of comprehensive evaluat…

cs.CV2025

AnyCap Project: A Unified Framework, Dataset, and Benchmark for Controllable Omni-modal Captioning

Yiming Ren, Zhiqiang Lin, Yu Li +8

Controllable captioning is essential for precise multimodal alignment and instruction following, yet existing models often lack fine-grained control and reliable evaluation protoco…

cs.CL2025

Unlocking Multimodal Mathematical Reasoning via Process Reward Model

Ruilin Luo, Zhuofan Zheng, Yifan Wang +9

Process Reward Models (PRMs) have shown promise in enhancing the mathematical reasoning capabilities of Large Language Models (LLMs) through Test-Time Scaling (TTS). However, their…

cs.CL2024

Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability

Zicheng Lin, Tian Liang, Jiahao Xu +7

Mathematical reasoning tasks pose significant challenges for large language models (LLMs) because they require precise logical deduction and sequence analysis. In this work, we int…