most citedTiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2026

GUITestScape: Towards Open-set Evaluation on Exploratory GUI Testing

Xiaoyi Chen, Yifei Gao, Yang Xu +3

Exploratory GUI testing is a particularly demanding setting for MLLM agents: without predefined test scripts, an agent must autonomously navigate an application and discover defect…

cs.CL2026

STAMP: Training Explicit Memory for Mobile GUI Agents in Controllable and Scalable Virtual Environments

Junyang Wang, Haiyang Xu, Xi Zhang +4

Mobile GUI agents excel at immediate reactive control but frequently fail in realistic, long-horizon tasks that require memory. This failure stems from a fundamental conflict betwe…

cs.AI2026

Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks

Yuxiang Zhang, Jiangming Shu, Ye Ma +3

Long-context Large Language Models, despite their expanded capacity, require careful working memory management to mitigate attention dilution during long-horizon tasks. Yet existin…

cs.CL20261 cited

TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents

Kai Li, Xuanqing Yu, Ziyi Ni +9

Long-horizon conversational agents have to manage ever-growing interaction histories that quickly exceed the finite context windows of large language models (LLMs). Existing memory…

cs.AI2026

Evaluate-as-Action: Self-Evaluated Process Rewards for Retrieval-Augmented Agents

Jiangming Shu, Yuxiang Zhang, Ye Ma +2

Retrieval-augmented agents can query external evidence, yet their reliability in multi-step reasoning remains limited: noisy retrieval may derail multi-hop question answering, whil…