most citedUI-Venus Technical Report: Building High-performance UI Agents with RFT

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cs.CV2026

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

Zhangxuan Gu, Haoxing Chen, Qi Qin +17

Diffusion large language models (dLLMs) achieve high decoding efficiency through block-parallel, arbitrary-order generation, making them attractive for latency-sensitive applicatio…

cs.CV2026

LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes

Chuyan Chen, Haoxing Chen, Kun Chen +27

We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understanding module built on the LLaDA…

cs.CV2026

UI-Venus-1.5 Technical Report

Venus Team, Changlong Gao, Zhangxuan Gu +24

GUI agents have emerged as a powerful paradigm for automating interactions in digital environments, yet achieving both broad generality and consistently strong task performance rem…

cs.CV2026

Unified Generation and Self-Verification for Vision-Language Models via Advantage Decoupled Preference Optimization

Xinyu Qiu, Heng Jia, Zhengwen Zeng +4

Parallel test-time scaling typically trains separate generation and verification models, incurring high training and inference costs. We propose Advantage Decoupled Preference Opti…

cs.CV2025

VenusBench-GD: A Comprehensive Multi-Platform GUI Benchmark for Diverse Grounding Tasks

Beitong Zhou, Zhexiao Huang, Yuan Guo +10

GUI grounding is a critical component in building capable GUI agents. However, existing grounding benchmarks suffer from significant limitations: they either provide insufficient d…

cs.CV2025

MVP: Multiple View Prediction Improves GUI Grounding

Yunzhu Zhang, Zeyu Pan, Zhengwen Zeng +3

GUI grounding, which translates natural language instructions into precise pixel coordinates, is essential for developing practical GUI agents. However, we observe that existing gr…

cs.CV2025★ 1 cited

UI-Venus Technical Report: Building High-performance UI Agents with RFT

Zhangxuan Gu, Zhengwen Zeng, Zhenyu Xu +21

We present UI-Venus, a native UI agent that takes only screenshots as input based on a multimodal large language model. UI-Venus achieves SOTA performance on both UI grounding and…