collaborators

8 papers

cs.AI2026

Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents

Zhijie Ding, Weinan Hong, Zicheng Zhu +6

Multimodal large language models (MLLMs) have substantially advanced mobile agents, yet proactive mobile assistance remains challenging because agents must decide \emph{when} to in…

cs.AI2026

ProactiveMobile: A Comprehensive Benchmark for Boosting Proactive Intelligence on Mobile Devices

Dezhi Kong, Zhengzhao Feng, Qiliang Liang +12

Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to a reactive paradigm, where…

cs.CL2026

ProUIE: A Macro-to-Micro Progressive Learning Method for LLM-based Universal Information Extraction

Wenda Liu, Zhigang Song, Shuai Nie +11

LLM-based universal information extraction (UIE) methods often rely on additional information beyond the original training data, which increases training complexity yet often yield…

cs.CV2026

GUI-CEval: A Hierarchical and Comprehensive Chinese Benchmark for Mobile GUI Agents

Yang Li, Yuchen Liu, Haoyu Lu +8

Recent progress in Multimodal Large Language Models (MLLMs) has enabled mobile GUI agents capable of visual perception, cross-modal reasoning, and interactive control. However, exi…

cs.CL2026

SSL: Sweet Spot Learning for Differentiated Guidance in Agentic Optimization

Jinyang Wu, Changpeng Yang, Yuhao Shen +9

Reinforcement learning with verifiable rewards has emerged as a powerful paradigm for training intelligent agents. However, existing methods typically employ binary rewards that fa…

cs.IR2026

Unified Multimodal and Multilingual Retrieval via Multi-Task Learning with NLU Integration

Xinyuan Zhang, Lina Zhang, Lisung Chen +6

Multimodal retrieval systems typically employ Vision Language Models (VLMs) that encode images and text independently into vectors within a shared embedding space. Despite incorpor…