activity
20242026
collaborators

43 papers

cs.AI2026

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

Long Zhang, Yuhan Chen, Chaoran Zhang +7

Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottlenecked by two fundamental is…

cs.CL2026

TRACE: A Self-Evolving Skill Bank for Consistent, Limit-Aware LLM Agents

Wenhao Wu, Menghao Zhang, Xin Wang +3

Reliable deployment of LLM agents in user-facing products depends not on raw task-solving ability but on consistency and limit-awareness: behaving the same way across repeated tria…

cs.CL2026

Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation

Chris Han, Pengzhi Gao, Pei Fu +1

We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models, we apply G…

cs.AI2026

G-ReAct: Graph-Guided Deep Search via Structure-State Co-Evolution

Shaoxiong Yang, Mengyuan Zhang, Shaojun Lin +4

Deep search has become a fundamental capability of large language models (LLMs) for solving open-domain complex tasks. However, existing approaches typically rely on linear sequent…

cs.AI2026

Mi-Memory: A Lifecycle Memory Framework for Personal AI

Xule Liu, Hanlin Teng, Chao Li +15

Personal AI is moving beyond chat-only interaction toward continuous services that span phones, cars, homes, wearables, cameras, and tools. In this setting, memory cannot remain a…

cs.LG2026

SEE: Structure-aware Exploring & Exploiting for Long-horizon GUI Agent Trajectory Synthesis

Zhuohang Fan, Beichen Zhang, Yuanfa Li +4

Graphical User Interface (GUI) agents powered by vision-language models hold promise for automating real-world mobile tasks. However, progress is limited by the lack of high-covera…