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From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

cs.CL2026

Metis: Memory Foundation Model

Zeyu Zhang, Ziliang Guo, Yihang Sun +14

The paper presents Metis, a memory foundation model that embeds a persistent, dynamically updated memory state within the model backbone, allowing it to store and retrieve informat…

cs.AI2026

DELTAMEM: Incremental Experience Memory for LLM Agents via Residual Trees

Haoran Tan, Zeyu Zhang, Zhicheng Cao +2

Large Language Model (LLM)-based agents increasingly rely on memory to learn from experiences over continual interactions. However, storing experiences as independent, flat units l…

cs.LG2026

Steering Frozen LLMs: Adaptive Social Alignment via Online Prompt Routing

Zeyu Zhang, Xiangxiang Dai, Ziyi Han +2

Large language models (LLMs) are typically governed by post-training alignment (e.g., RLHF or DPO), which yields a largely static policy during deployment and inference. However, r…

cs.AI2026

NextMem: Towards Latent Factual Memory for LLM-based Agents

Zeyu Zhang, Rui Li, Xiaoyan Zhao +4

Memory is critical for LLM-based agents to preserve past observations for future decision-making, where factual memory serves as its foundational part. However, existing approaches…

cs.AI2026

Towards Adaptive, Scalable, and Robust Coordination of LLM Agents: A Dynamic Ad-Hoc Networking Perspective

Rui Li, Zeyu Zhang, Xiaohe Bo +4

Multi-agent architectures built on large language models (LLMs) have demonstrated the potential to realize swarm intelligence through well-crafted collaboration. However, the subst…

cs.AI2025

Explicit v.s. Implicit Memory: Exploring Multi-hop Complex Reasoning Over Personalized Information

Zeyu Zhang, Yang Zhang, Haoran Tan +2

In large language model-based agents, memory serves as a critical capability for achieving personalization by storing and utilizing users' information. Although some previous studi…