3 papers
cs.AI2026
Learning What to Share and What to Personalize: Hierarchical Strategy Co-Evolution for Agent Memory
Yupeng Han, Shuochen Liu, Kai Zhang +3
Memory-augmented agents maintain compact user profiles throughout extended conversations, enabling personalized and consistent responses without the need to process the entire dial…
cs.AI2026
Meta-Task: Turning Terminal Task Synthesis into a Terminal Task for Scalable Agent Training
Zhihong Pan, Jiyuan He, Kai Zhang +5
Training terminal agents at scale requires diverse, verifiable terminal tasks and high-quality interaction trajectories, yet acquiring such data remains a significant challenge. Ex…
cs.IR2025
From Entity Reliability to Clean Feedback: An Entity-Aware Denoising Framework Beyond Interaction-Level Signals
Ze Liu, Xianquan Wang, Shuochen Liu +5
Implicit feedback is central to modern recommender systems but is inherently noisy, often impairing model training and degrading user experience. At scale, such noise can mislead l…