2 papers
cs.LG2026
MemoWM: How World Models Change What Agents Need to Remember
Bingfan Zeng, Zhisheng Chen, Chenbo Sang +6
Long-term agents face growing storage demands as they accumulate experience. World models capture reusable regularities that can reduce the information stored for each experience.…
cs.AI2026
MemPrism: Task-Conditioned Relational Memory Views for Long-Horizon Agents
Zhisheng Chen, Bingfan Zeng, Bangde Cao +8
Long-horizon agents rely on memory to reuse experiences, yet existing memory systems often assume that evidence can be directly consumed through a fixed representation. This leads…