activity
20232026
most citedQwen Technical Report

110 citations · 372 across the 29 of their papers we have counts for

collaborators

31 papers

cs.AI2026

AUV-Bench: Aesthetic Understanding and Generation Evaluation for User Interfaces

Zhijie Deng, Ling Li, Junhao Ji +7

Multimodal foundation models are increasingly used for evaluating and generating user interfaces (UIs), often producing seemingly reasonable aesthetic judgments and visually plausi…

cs.CL2026

RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents

Shuai Bai, Jiayong Deng, Sicheng Fan +30

Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Real digital work requires both…

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.LG2026

Qwen-CUA: Native Computer Use for (almost) Everything

Dunjie Lu, Shuai Bai, Tianyi Bai +42

Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking, large-scale interactive expe…

cs.CV2026

Contrastive On-Policy Distillation

Jiacheng Ruan, Jun Tang, Wenzhen Yuan +5

On-policy distillation (OPD) trains a student model on trajectories sampled from its own policy, providing dense token-level supervision by minimizing the divergence between the te…

cs.AI2026

CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents

Bowen Wang, Dunjie Lu, Junli Wang +11

Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its extension to computer-use agents…

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.CV2026

Qwen-Image-2.0 Technical Report

Bing Zhao, Chenfei Wu, Deqing Li +72

We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…

cs.RO2026

FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies

Xintong Hu, Xuhong Huang, Jinyu Zhang +11

Vision-Language-Action (VLA) models are increasingly expected to not only complete robot tasks, but also follow human instructions about how those tasks should be executed. However…

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.AI2026

Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

Haiyang Xu, Xi Zhang, Haowei Liu +16

The paper introduces GUI-Owl-1.5, the latest native GUI agent model that features instruct/thinking variants in multiple sizes (2B/4B/8B/32B/235B) and supports a range of platforms…

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

VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models

Jianke Zhang, Xiaoyu Chen, Qiuyue Wang +7

Vision-Language-Action (VLA) models, which integrate pretrained large Vision-Language Models (VLM) into their policy backbone, are gaining significant attention for their promising…

cs.CV2025

VLCache: Computing 2% Vision Tokens and Reusing 98% for Vision-Language Inference

Shengling Qin, Hao Yu, Chenxin Wu +10

This paper presents VLCache, a cache reuse framework that exploits both Key-Value (KV) cache and encoder cache from prior multimodal inputs to eliminate costly recomputation when t…

cs.LG2025

Soft Adaptive Policy Optimization

Chang Gao, Chujie Zheng, Xiong-Hui Chen +7

Reinforcement learning (RL) plays an increasingly important role in enhancing the reasoning capabilities of large language models (LLMs), yet stable and performant policy optimizat…

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…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CV2025

Revisiting Multimodal Positional Encoding in Vision-Language Models

Jie Huang, Xuejing Liu, Sibo Song +4

Multimodal position encoding is essential for vision-language models, yet there has been little systematic investigation into multimodal position encoding. We conduct a comprehensi…

cs.CL2025★ 2 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.CV2025

FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark

Rongyao Fang, Aldrich Yu, Chengqi Duan +7

The advancement of open-source text-to-image (T2I) models has been hindered by the absence of large-scale, reasoning-focused datasets and comprehensive evaluation benchmarks, resul…

cs.CV2025★ 2 cited

Qwen-Image Technical Report

Chenfei Wu, Jiahao Li, Jingren Zhou +36

We present Qwen-Image, an image generation foundation model in the Qwen series that achieves significant advances in complex text rendering and precise image editing. To address th…

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…

cs.CL2025★ 12 cited

Qwen2.5-Omni Technical Report

Jin Xu, Zhifang Guo, Jinzheng He +11

In this report, we present Qwen2.5-Omni, an end-to-end multimodal model designed to perceive diverse modalities, including text, images, audio, and video, while simultaneously gene…

cs.CV2025

Multimodal Representation Alignment for Image Generation: Text-Image Interleaved Control Is Easier Than You Think

Liang Chen, Shuai Bai, Wenhao Chai +5

The field of advanced text-to-image generation is witnessing the emergence of unified frameworks that integrate powerful text encoders, such as CLIP and T5, with Diffusion Transfor…