activity
20152026
most citedTextField: Learning A Deep Direction Field for Irregular Scene Text Detection

370 citations · 522 across the 44 of their papers we have counts for

collaborators

48 papers

cs.CV2026

DocClaw: A Unified Agentic System for Intelligent Document Processing

Siqi Xiang, Zhipeng Xu, Yufei Liu +6

Intelligent document processing (IDP) encompasses a broad range of tasks, including optical character recognition (OCR), document question answering (DocQA), and key information ex…

cs.AI2026

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery

Taolin Han, Yuchen Zhang, Jinghang Wang +22

Large language models (LLMs) are increasingly involved in scientific discovery, yet it remains unclear whether they can support complex real laboratory science. Here we introduce S…

cs.CL2026

EntSQL: A Benchmark for Grounding Text-to-SQL in Long-Context Enterprise Knowledge

Chengxi Liao, Tao Xu, Zulong Chen +7

Text-to-SQL enables natural language access to databases, and recent LLMs have substantially advanced its capabilities. Existing benchmarks such as Spider, BIRD, and Spider~2.0 eva…

cs.LG2026

More Than Memory: Task-Conditioned Signed FFN Writes in Long-Context Retrieval

Zhibo Yang

FFNs are often treated as parametric memories. In long-context retrieval, however, the sharper question is not only what they store, but whether their native residual writes push t…

cs.RO2026

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Qiuyue Wang, Mingsheng Li, Jian Guan +37

Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented capabilities and limited generali…

cs.AI2026

MPDocBench-Parse: Benchmarking Practical Multi-page Document Parsing

Bangbang Zhou, Hangdi Xing, Yifan Chen +8

Document parsing converts visually rich documents into machine-readable structured representations, forming a crucial foundation for information systems. Although many benchmarks h…

cs.CL2026

Multi-domain Multi-modal Document Classification Benchmark with a Multi-level Taxonomy

Denghao Ma, Qing Liu, Zulong Chen +5

Document classification forms the backbone of modern enterprise content management, yet existing benchmarks remain trapped in oversimplified paradigms -- single domain settings wit…

cs.CL2026

CC-OCR V2: Fine-Grained Attribution of LMM Failures in Real-World Visual Document Understanding

Chunyi Peng, Zhipeng Xu, Yuqi Xiong +12

Recent Large Multimodal Models (LMMs) have achieved remarkable progress on OCR-centric document understanding and processing tasks. Existing benchmarks primarily evaluate LMMs acro…

cs.CL2026

Triviality Corrected Endogenous Reward

Xinda Wang, Zhengxu Hou, Yangshijie Zhang +6

Reinforcement learning for open-ended text generation is constrained by the lack of verifiable rewards, necessitating reliance on judge models that require either annotated data or…

cs.CV2026

Learning Transferable Temporal Primitives for Video Reasoning via Synthetic Videos

Songtao Jiang, Sibo Song, Chenyi Zhou +12

The transition from image to video understanding requires vision-language models (VLMs) to shift from recognizing static patterns to reasoning over temporal dynamics such as motion…

cs.CV2026

From Narrow to Panoramic Vision: Attention-Guided Cold-Start Reshapes Multimodal Reasoning

Ruilin Luo, Chufan Shi, Yizhen Zhang +10

The cold-start initialization stage plays a pivotal role in training Multimodal Large Reasoning Models (MLRMs), yet its mechanisms remain insufficiently understood. To analyze this…

cs.CV2026

CodePercept: Code-Grounded Visual STEM Perception for MLLMs

Tongkun Guan, Zhibo Yang, Jianqiang Wan +10

When MLLMs fail at Science, Technology, Engineering, and Mathematics (STEM) visual reasoning, a fundamental question arises: is it due to perceptual deficiencies or reasoning limit…

cs.CV2026

UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents

Yifan Ji, Zhipeng Xu, Zhenghao Liu +7

Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual quality, and task-specific information req…

cs.CL2026★ 2 cited

Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking

Mingxin Li, Yanzhao Zhang, Dingkun Long +9

In this report, we introduce the Qwen3-VL-Embedding and Qwen3-VL-Reranker model series, the latest extensions of the Qwen family built on the Qwen3-VL foundation model. Together, t…

cs.CV2026★ 1 cited

BabyVision: Visual Reasoning Beyond Language

Liang Chen, Weichu Xie, Yiyan Liang +27

While humans develop core visual skills long before acquiring language, contemporary Multimodal LLMs (MLLMs) still rely heavily on linguistic priors to compensate for their fragile…

cs.CV2025★ 16 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★ 1 cited

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

Songtao Jiang, Yuan Wang, Sibo Song +22

Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…

cs.CL2025

Layout-Aware Parsing Meets Efficient LLMs: A Unified, Scalable Framework for Resume Information Extraction and Evaluation

Fanwei Zhu, Jinke Yu, Zulong Chen +6

Automated resume information extraction is critical for scaling talent acquisition, yet its real-world deployment faces three major challenges: the extreme heterogeneity of resume…

cs.CV2025

DocThinker: Explainable Multimodal Large Language Models with Rule-based Reinforcement Learning for Document Understanding

Wenwen Yu, Zhibo Yang, Yuliang Liu +1

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in document understanding. However, their reasoning processes remain largely black-box, making it…

cs.CL2025

EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance Generation

Xinda Wang, Zhengxu Hou, Yangshijie Zhang +6

Although the effectiveness of Large Language Models (LLMs) as judges (LLM-as-a-judge) has been validated, their performance remains limited in open-ended tasks, particularly in sto…

cs.CV2025

Generative Compositor for Few-Shot Visual Information Extraction

Zhibo Yang, Wei Hua, Sibo Song +4

Visual Information Extraction (VIE), aiming at extracting structured information from visually rich document images, plays a pivotal role in document processing. Considering variou…

cs.CV2025★ 82 cited

Qwen2.5-VL Technical Report

Shuai Bai, Keqin Chen, Xuejing Liu +24

We introduce Qwen2.5-VL, the latest flagship model of Qwen vision-language series, which demonstrates significant advancements in both foundational capabilities and innovative func…

cs.CV2025★ 2 cited

OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models

Wenwen Yu, Zhibo Yang, Jianqiang Wan +5

Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understanding and the emergence of large language…

cs.CV2025

SceneVTG++: Controllable Multilingual Visual Text Generation in the Wild

Jiawei Liu, Yuanzhi Zhu, Feiyu Gao +5

Generating visual text in natural scene images is a challenging task with many unsolved problems. Different from generating text on artificially designed images (such as posters, c…