collaborators
Showing cs.AIShow all

7 papers · 1 filter

cs.AI2026

Task-Adaptive Rubrics for GUI Reward Modeling

Tao Xiong, Xavier Hu, Wenkai Wang +6

Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajectory satisfies the success cri…

cs.AI2026

DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration

Wenkai Wang, Tao Xiong, Jingchen Ni +6

Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop coordination, where agents…

cs.AI2026

Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration

Weile Chen, Bingchen Miao, Qifan Yu +6

Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on handcrafted execution pipelines…

cs.AI2025

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

Reuben Tan, Baolin Peng, Zhengyuan Yang +15

Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally optimized using sparse, outcome-bas…

cs.AI2025

GUI-PRA: Process Reward Agent for GUI Tasks

Tao Xiong, Xavier Hu, Yurun Chen +6

Long-horizon GUI automation remains challenging due to error accumulation over extended interaction sequences. Process Reward Models (PRMs) provide dense step-level supervision for…

cs.AI2025

OS Agents: A Survey on MLLM-based Agents for General Computing Devices Use

Xueyu Hu, Tao Xiong, Biao Yi +26

The dream to create AI assistants as capable and versatile as the fictional J.A.R.V.I.S from Iron Man has long captivated imaginations. With the evolution of (multi-modal) large la…

cs.AI2025

Efficient Agents: Building Effective Agents While Reducing Cost

Ningning Wang, Xavier Hu, Pai Liu +11

The remarkable capabilities of Large Language Model (LLM)-driven agents have enabled sophisticated systems to tackle complex, multi-step tasks, but their escalating costs threaten…