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20242026
most citedA Survey on the Memory Mechanism of Large Language Model based Agents

11 citations · 14 across the 11 of their papers we have counts for

collaborators

14 papers

cs.AI2026

ARCO: Adaptive Rubrics with Co-Evolution for Multi-Step LLM-Based Agents

Zihang Tian, Jingsen Zhang, Rui Li +3

Reinforcement learning for multi-step LLM agents often relies on scalar rewards that indicate success but cannot explain why a trajectory is good or bad. Rubric-based rewards impro…

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.CL2026

HAPS: Hierarchical LLM Routing with Joint Architecture and Parameter Search

Zihang Tian, Rui Li, Jingsen Zhang +3

Large language model (LLM) routing aims to exploit the specialized strengths of different LLMs for diverse tasks. However, existing approaches typically focus on selecting LLM arch…

cs.CL2025

CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension

Rui Li, Zeyu Zhang, Xiaohe Bo +5

Current Large Language Models (LLMs) are confronted with overwhelming information volume when comprehending long-form documents. This challenge raises the imperative of a cohesive…

cs.CL2025

Prompt and Parameter Co-Optimization for Large Language Models

Xiaohe Bo, Rui Li, Zexu Sun +5

Prompt optimization and fine-tuning are two major approaches to improve the performance of Large Language Models (LLMs). They enhance the capabilities of LLMs from complementary pe…

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…

cs.LG2025★ 1 cited

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Zeyu Zhang, Quanyu Dai, Rui Li +3

LLM-based agents have been extensively applied across various domains, where memory stands out as one of their most essential capabilities. Previous memory mechanisms of LLM-based…

cs.CL2025

KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing

Rui Li, Quanyu Dai, Zeyu Zhang +3

Recent advances in retrieval-augmented generation (RAG) furnish large language models (LLMs) with iterative retrievals of relevant information to handle complex multi-hop questions…

cs.AI2025

MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents

Zeyu Zhang, Quanyu Dai, Xu Chen +3

Recently, large language model based (LLM-based) agents have been widely applied across various fields. As a critical part, their memory capabilities have captured significant inte…

cs.SI2024★ 2 cited

TrendSim: Simulating Trending Topics in Social Media Under Poisoning Attacks with LLM-based Multi-agent System

Zeyu Zhang, Jianxun Lian, Chen Ma +9

Trending topics have become a significant part of modern social media, attracting users to participate in discussions of breaking events. However, they also bring in a new channel…

cs.AI2024

MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants

Zeyu Zhang, Quanyu Dai, Luyu Chen +7

LLM-based agents have been widely applied as personal assistants, capable of memorizing information from user messages and responding to personal queries. However, there still lack…

cs.LG2024

Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization

Rui Li, Chaozhuo Li, Yanming Shen +2

Recent advances in knowledge graph embedding (KGE) rely on Euclidean/hyperbolic orthogonal relation transformations to model intrinsic logical patterns and topological structures.…

cs.AI2024★ 11 cited

A Survey on the Memory Mechanism of Large Language Model based Agents

Zeyu Zhang, Xiaohe Bo, Chen Ma +6

Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are feature…