Persistent Memory for Language Models

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35 papers in the last four weeks, up 400% on the four weeks before. 0.3% of all new papers.

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The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory
Jun 30, 2026Zihan Chen, Songwei Dong, Chengshuai Shi +4Continual Learning for LLM Agents Persistent Memory for Language Models
University of Virginia · Princeton University · University of Central Florida
Mandol: An Agglomerative Agent Memory System for Long-Term Conversations
Jun 29, 2026Yuhan Zhang, Zhiyuan Guo, Ziheng Zeng +3Agent Memory Graph Retrieval-Augmented Generation
Institute of Software, Chinese Academy of Sciences · Microsoft Research
Selective Memory Retention for Long-Horizon LLM Agents
Jun 28, 2026Pranath ReddyLLM Agent Memory Persistent Memory for Language Models
Independent Researcher, Huntsville, Alabama, USA.
Memory Depth, Not Memory Access: Selective Parametric Consolidation for Long-Running Language Agents
Jun 25, 2026Haoliang HanAgent Memory Continual Learning for LLM Agents
Institute of Biomedical Strategy, China Pharmaceutical University
ConvMemory v3: A Validity Context Layer for Conversational Memory via Target-Conditioned Relation Verification
Jun 25, 2026Taiheng PanConversational Memory Persistent Memory for Language Models
School of Computing and Information Systems University of Melbourne
Reclaim Evaluation: A Lossy Memory Is Worse Than an Empty One
Jun 24, 2026Alex KwonLLM Evaluation Memory-Augmented Language Models
Independent Researcher
ATMA: Length-Invariant Language Modeling via Polar Attention and Gated-Delta Compression Memory
Jun 23, 2026Habibullah AkbarMemory-Augmented Language Models Long-Context Language Modeling
Kreasof AI Jakarta, Indonesia
DynamicMem: A Long-Horizon Memory Benchmark in Real-World Settings
Jun 22, 2026Wenya Xie, Shengming Zhou, Zelin Li +9Agent Memory LLM Agent Memory
University of Minnesota · University of North Carolina at Charlotte · Johns Hopkins University +2
When Does Belief-Based Agent Memory Help? Reliability-Conditional Updating and Provenance-Capped Poisoning Defense
Jun 20, 2026Pranav SinghAgent Memory Bayesian Inference
Indian Institute of Technology Ropar
AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents
Jun 19, 2026Xingyu Chen, Rui Wang, Zhaopeng Tu +1LLM Agent Memory Persistent Memory for Language Models
Shanghai Jiao Tong University, Tencent · Shanghai Jiao Tong University · Tencent
Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning
Jun 18, 2026Nusrat Jahan Lia, Aritra MazumderPersistent Memory for Language Models Long-Term Conversational Memory
Institute of Information Technology University of Dhaka, Dhaka, Bangladesh · University of Utah Utah, USA
Latent Personal Memory: Represent personal memory as dynamic soft prompts
Jun 18, 2026Debrup Das, Avinash Amballa, Yashas Malur Saidutta +3LLM Inference Efficiency Memory-Efficient Fine-Tuning
University of Massachusetts Amherst · Samsung Research America
AtomMem: Building Simple and Effective Memory System for LLM Agents via Atomic Facts
Jun 18, 2026Yanyu Yao, Shangze Li, Zhi Zheng +4Persistent Memory for Language Models Long-Term Conversational Memory
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China, Hefei, China · Anhui University, Hefei, China
User as Engram: Internalizing Per-User Memory as Local Parametric Edits
Jun 17, 2026Bojie LiKnowledge Editing LLM Personalization
Pine AI
Continual Self-Improvement with Lightweight Experiential Latent Memories
Jun 16, 2026Vaggelis Dorovatas, Nancy Kalaj, Rahaf AljundiContinual Learning for LLMs Memory-Augmented Language Models
Toyota Motor Europe · University of Trento
MemTrace: Probing What Final Accuracy Misses in Long-Term Memory
Jun 15, 2026Xianxuan Long, Zhikai Chen, Shenglai Zeng +3Temporal Reasoning in Language Models LLM Agent Memory
Michigan State University · Case Western Reserve University
User as Code: Executable Memory for Personalized Agents
Jun 15, 2026Bojie LiPersistent Memory for Language Models Knowledge Representation
Pine AI
DYNA : Dynamic Episodic Memory Networks for Augmenting Large Language Models with Temporal Knowledge Graphs in Continuous Learning
Jun 14, 2026Ali Sarabadani, Mahtab TajvidiyanContinual Learning for LLMs Memory-Augmented Language Models
Department of Computer Engineering and Information Technology, University of Qom, Qom, Iran
The Reservoir Attention Network: Cross-Pass State in Pretrained Transformers via Content-Addressable Reservoir Injection
Jun 14, 2026Emma LeonhartMemory-Augmented Neural Networks Persistent Memory for Language Models
T-Mem: Memory That Anticipates, Not Archives
Jun 13, 2026Weidong Guo, Dakai Wang, Zixuan Wang +2Persistent Memory for Language Models LLM Memory
1Tencent · 2The Hong Kong University of Science and Technology (Guangzhou)
GitOfThoughts: Version-Controlled Reasoning and Agent Memory You Can Replay, Diff, and Merge
Jun 12, 2026Pavan C Shekar, Abhishek H S, Aswanth KrishnanLLM Agent Memory Persistent Memory for Language Models
QpiAI, Bengaluru, India
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
Jun 11, 2026Minjae Kim, Jinheon Baek, Soyeong Jeong +1Persistent Memory for Language Models Long-Term Conversational Memory
Korea University · KAIST
Learning What to Remember: A Cognitively Grounded Multi-Factor Value Model for Agentic Memory
Jun 11, 2026Zhibao Chen, Qian ChengLLM Agent Memory Persistent Memory for Language Models
Huatai Securities, Nanjing, China
Multi-Turn Reasoning When Context Arrives in Pieces: Scalable Sharding and Memory-Augmented RL
Jun 11, 2026Shu Tong Luo, Wenqin Liu, Rui Liu +2Memory-Augmented Language Models RL for Language Model Reasoning
The University of Melbourne · The University of Tokyo
Substrate Asymmetry in User-Side Memory: A Diagnostic Framework
Jun 10, 2026Youwang DengRetrieval-Augmented Generation LLM Personalization
EpistemicaLab — Independent Research
REAL: A Reasoning-Enhanced Graph Framework for Long-Term Memory Management of LLMs
Jun 9, 2026Keer Lu, Liwei Chen, Guoqing Jiang +3Conversational Memory Persistent Memory for Language Models
School of Computer Science, Peking University · Kuaishou Technology · Center for Data Science, Academy for Advanced Interdisciplinary Studies, Peking University
Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory
Jun 9, 2026Suozhao Ji, Baodong Wu, Zehao Wang +8LLM Agent Memory Persistent Memory for Language Models
1Infinigence AI · 2Tsinghua University · 3Shanghai Jiaotong University
Deployment-Time Memorization in Foundation-Model Agents
Jun 8, 2026Lei, Chen, Guilin Zhang +8Persistent Memory for Language Models Privacy Leakage in Language Models
Rachel
Why Limit the Residual Stream to Layers and Not Tokens? Persistent Memory for Continuous Latent Reasoning
Jun 5, 2026Mujtaba Farhan, Maheep ChaudharyMemory-Augmented Language Models Persistent Memory for Language Models
1Algoverse AI Research · 2Independent
Rosetta Memory: Adaptive Memory for Cross-LLM Agents
Jun 5, 2026Hao Yang, Shiqi Shen, Haoxuan Li +3LLM Agent Memory Persistent Memory for Language Models
Gaoling School of Artificial Intelligence, Renmin University of China · Weixin, Tencent · Institute for Artificial Intelligence, Peking University

Jun 30, 2026, cs.AIJ/K move · Enter open · S save

The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory

Zihan Chen, Songwei Dong, Chengshuai Shi, Peng Wang+3

University of Virginia · Princeton University · University of Central Florida

Continual Learning for LLM Agents Persistent Memory for Language Models LLM Memory Agent Memory Management Memory-Augmented Language Model Agents

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Sequentially evolving LLM memory enables agents to reuse past experience, but existing systems usually deploy each locally generated memory update without checking whether it improves future behavior. As a result, updates that help the current task may overwrite useful knowledge, introduce over-specific rules, or bias the final memory toward recent examples. We propose Janus, a plug-in memory controller that decides whether to accept a candidate memory update or retain the previous memory. To make this decision efficient, Janus uses a Memory Momentum Trigger to identify suspicious deviations in the memory-update trajectory, and compares old and new memories on a compact hybrid evaluation set of coverage, boundary, and fresh tasks instead of replaying the full history. Janus is method-agnostic and wraps existing updaters without changing their update rules. Across six datasets, two backbone LLMs, and two memory updaters, Janus improves average accuracy by +2.7 to +4.6 points over the corresponding base updaters.

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