4 papers · 1 filter
ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Gaole Dai, Shiqi Jiang, Ting Cao +5
Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents,…
ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations
Zilong Wang, Nan Chen, Luna K. Qiu +6
Global aging calls for scalable and engaging cognitive interventions. Computerized cognitive training (CCT) is a promising non-pharmacological approach, yet many unsupervised progr…
Advancing Mobile GUI Agents: A Verifier-Driven Approach to Practical Deployment
Gaole Dai, Shiqi Jiang, Ting Cao +5
We propose V-Droid, a mobile GUI task automation agent. Unlike previous mobile agents that utilize Large Language Models (LLMs) as generators to directly generate actions at each s…
Co-Sight: Enhancing LLM-Based Agents via Conflict-Aware Meta-Verification and Trustworthy Reasoning with Structured Facts
Hongwei Zhang, Ji Lu, Shiqing Jiang +11
Long-horizon reasoning in LLM-based agents often fails not from generative weakness but from insufficient verification of intermediate reasoning. Co-Sight addresses this challenge…