4 papers
RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models
Xiao Feng, Bo Han, Zhanke Zhou +5
Reinforcement learning (RL) shows promise for enhancing LLM agentic reasoning, yet sparse terminal rewards hinder fine-grained optimization. Process reward modeling offers an alter…
TVWorld: Foundations for Remote-Control TV Agents
Zhantao Ma, Quanfeng Lu, Shuai Zhong +3
Recent large vision-language models (LVLMs) have demonstrated strong potential for device control. However, existing research has primarily focused on point-and-click (PnC) interac…
SWIRL: A Staged Workflow for Interleaved Reinforcement Learning in Mobile GUI Control
Quanfeng Lu, Zhantao Ma, Shuai Zhong +4
The rapid advancement of large vision language models (LVLMs) and agent systems has heightened interest in mobile GUI agents that can reliably translate natural language into inter…
NLAFormer: Transformers Learn Numerical Linear Algebra Operations
Zhantao Ma, Yihang Gao, Michael K. Ng
Transformers are effective and efficient at modeling complex relationships and learning patterns from structured data in many applications. The main aim of this paper is to propose…