2 papers
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…
cs.CL2026
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…