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cs.AI2026

DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents

Yu Liu, Zhilin Liu, Zhiwei Yang +7

As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to assess multimodal perception,…

cs.AI2026

Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models

Xingming Long, Yu Liu, Zhiwei Yang +7

Modern vision-language models (VLMs) can directly answer many image-grounded questions, yet they often struggle with complex queries requiring fine-grained visual details or extern…

cs.AI2026

Xiaomi-GUI-0 Technical Report

Wanxia Cao, Chengzhen Duan, Pei Fu +29

Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, tex…

cs.AI2026

EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models

Yiyang Fang, Wenke Huang, Pei Fu +5

Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual reasoning and understanding tasks but still struggle to capture the complexity and subjectivity of…

cs.AI2026

GAIA: A Data Flywheel System for Training GUI Test-Time Scaling Critic Models

Shaokang Wang, Pei Fu, Ruoceng Zhang +7

While Large Vision-Language Models (LVLMs) have significantly advanced GUI agents' capabilities in parsing textual instructions, interpreting screen content, and executing tasks, a…