Memory-Augmented Language Models

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29 papers in the last four weeks, up 142% on the four weeks before. 0.3% of all new papers.

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Latest papers 193

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Connecting the Dots: Benchmarking Reflective Memory in Long-Horizon Dialogue
May 31, 2026Jingjie Lin, Bingbing Wang, Zihan Wang +4Memory-Augmented Language Models Long-Context Modeling
Harbin Institute of Technology, Shenzhen · The Hong Kong Polytechnic University · Fudan University +1
KACE: Knowledge-Adaptive Context Engineering for Mathematical Reasoning
May 30, 2026Jayant Parashar, Suchendra M. BhandarkarMemory-Augmented Language Models Self-Consistency Decoding
School of Computing University of Georgia
LLMs Need Encoders for Semantic IDs Too
May 29, 2026Xiangyi Chen, Zelun Wang, Xinyi Li +3Memory-Augmented Language Models Generative Recommendation
Pinterest · United States
Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory
May 29, 2026Han Zhang, Zihao Tang, Xin Yu +8LLM Evaluation Memory-Augmented Language Models
Center for Applied Statistics, Renmin University of China · School of Statistics, Renmin University of China · Microsoft
Unlocking the Working Memory of Large Language Models for Latent Reasoning
May 28, 2026Lukas Aichberger, Sepp HochreiterMemory-Augmented Language Models Efficient Language Model Reasoning
ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria · NXAI GmbH, Linz, Austria
HTAM: Hierarchical Transition-Attended Memory for Operator Optimization
May 28, 2026Yining Zhang, Mingyang Yi, Chen Wang +5GPU Kernel Optimization Memory-Augmented Language Models
School of Artificial Intelligence, University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences · Zhongguancun Academy +1
VikingMem: A Memory Base Management System for Stateful LLM-based Applications
May 28, 2026Jiajie Fu, Junwen Chen, Mengzhao Wang +5Memory-Augmented Language Models Persistent Memory for Language Models
Zhejiang University · China · ByteDance
Knowledge Offloading: Decomposing LLMs into Sparse Backbones and Memory Modules
May 27, 2026Karim Galliamov, Rochelle Choenni, Ivan TitovLLM Pruning LLM Compression
University of Amsterdam · University of Edinburgh
MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems
May 27, 2026Xinle Deng, Ruobin Zhong, Hujin Peng +15LLM Evaluation Memory-Augmented Language Models
Zhejiang University · Alibaba Group
Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity
May 27, 2026Xiuying Wei, Caglar GulcehreMemory-Augmented Language Models Self-Attention
EPFL, CLAIRE Lausanne, Switzerland
Context Distillation as Latent Memory Management
May 27, 2026Ziyang Zheng, Zeju Li, Xiangyu Wen +5Memory-Augmented Language Models Language Model Distillation
The Chinese University of Hong Kong · Huawei Noah’s Ark Lab
MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models
May 27, 2026Hyeonjeong Ha, Jeonghwan Kim, Cheng Qian +7Memory-Augmented Language Models LLM Hallucination Mitigation
University of Illinois Urbana-Champaign · Capital One · Columbia University
Tensor Memory: Fixed-Size Recurrent State for Long-Horizon Transformers
May 26, 2026Kabir Swain, Sijie Han, Daniel Karl I. Weidele +2Memory-Augmented Neural Networks Memory-Augmented Language Models
Massachusetts Institute of Technology, Cambridge, MA, USA · University of Toronto, Toronto, Canada · IBM Research, Cambridge, MA, USA
Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference
May 25, 2026Sangyun Lee, Sean McLeish, Tom Goldstein +1Memory-Augmented Language Models Long-Context Language Model Inference
Carnegie Mellon University · University of Maryland
Simulating Human Memory with Language Models
May 25, 2026Qihan Wang, Nicholas Tomlin, Michael Hu +2LLM Evaluation Memory-Augmented Language Models
NYU · UMass Amherst
IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference
May 25, 2026Xintong Yang, Hao Gu, Binxing Xu +6Memory-Augmented Language Models Self-Attention
The Hong Kong University of Science and Technology · Zhejiang University
H $^{2}$ MT: Semantic Hierarchy-Aware Hierarchical Memory Transformer
May 24, 2026Maryam Haghifam, Zifan He, Jason Cong +1Memory-Augmented Language Models Long-Context Language Model Inference
University of California, Los Angeles USA
Lngram: N-gram Conditional Memory in Latent Space
May 24, 2026Yunao Zheng, Guoyang Xia, Xiaojie Wang +1Memory-Augmented Language Models Long-Context Language Modeling
Beijing University of Posts and Telecommunications (BUPT), Beijing, China · Li Auto Inc., Beijing, China
WhenLoss: Diagnosing Write and Retrieval Bottlenecks in Long-Context Memory Systems
May 23, 2026Jiangnan Yu, Kisson Songqi Lin, Jilong WuLong-Context Retrieval Memory-Augmented Language Models
FD-RAG: Federated Dual-System Retrieval-Augmented Generation
May 22, 2026Tianhao Gao, Kai Yang, Yiyang LiRetrieval-Augmented Generation Memory-Augmented Language Models
School of Computer Science and Technology, Tongji University
Dynamic Mixture of Latent Memories for Self-Evolving Agents
May 21, 2026Dianzhi Yu, Vireo Zhang, Hongru Wang +7Continual Learning for LLMs Mixture-of-Experts Language Models
The Chinese University of Hong Kong · Nanyang Technological University · University of Edinburgh +2
Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory
May 20, 2026Runxi Cheng, Yuchen Guan, Yongxian Wei +7Language Model Pretraining Memory-Augmented Language Models
Tsinghua University · Microsoft Reasearch Asia
From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG
May 18, 2026Changmin Lee, Jaemin Kim, Taesik GongRetrieval-Augmented Generation Memory-Augmented Language Models
Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Context Memorization for Efficient Long Context Generation
May 18, 2026Yasuyuki Okoshi, Hao Mark Chen, Guanxi Lu +3Memory-Augmented Language Models Long-Context Language Model Inference
Institute of Science Tokyo, Japan · Imperial College London, UK
NGM: A Plug-and-Play Training-Free Memory Module for LLMs
May 16, 2026Yuwen Qu, Wenhui Dong, Chenyang Si +1Memory-Augmented Language Models Knowledge Augmentation for Language Models
Nanjing University
Recall Isn't Enough: Bounding Commitments in Personalized Language Systems
May 15, 2026Rui Tang, Yichi Zhang, Xi Chen +4Memory-Augmented Language Models Controllable Text Generation
OpenAsk · Stern School of Business, New York University · Bank of Hebei +4
Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory
May 14, 2026Songwei Dong, Zihan Chen, Chengshuai Shi +3Continual Learning for LLMs LLM Evaluation
University of Virginia · Princeton University
MeMo: Memory as a Model
May 14, 2026Ryan Wei Heng Quek, Sanghyuk Lee, Alfred Wei Lun Leong +6Retrieval-Augmented Generation Memory-Augmented Language Models
Institute of Data Science, National University of Singapore, Singapore · Integrative Sciences and Engineering Programme, NUSGS, Singapore · Agency for Science, Technology, Research (A*STAR), Singapore +6
Improving Multi-turn Dialogue Consistency with Self-Recall Thinking
May 14, 2026Renning Pang, Tian Lan, Leyuan Liu +3Memory-Augmented Language Models Long-Term Conversational Memory
University of Electronic Science and Technology of China
Emotion-Attended Stateful Memory (EASM):The Architecture for Hyper-Personalization at Scale
May 14, 2026Vineet Kotecha, Vansh GuptaMemory-Augmented Language Models Personalized Language Models
divAIne Research

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Connecting the Dots: Benchmarking Reflective Memory in Long-Horizon Dialogue

Jingjie Lin, Bingbing Wang, Zihan Wang, Zhengda Jin+3

Harbin Institute of Technology, Shenzhen · The Hong Kong Polytechnic University · Fudan University+1

Memory-Augmented Language Models Long-Context Modeling Long-Term Conversational Memory

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Despite substantial progress in long-context modeling, existing benchmarks remain confined to factual memory for explicit recall, failing to measure the reflective memory required to synthesize fragmented, multimodal cues into high-level interpretations. To address this gap, we introduce RefMem-Bench, a benchmark for reflective memory in long-horizon dialogue. RefMem-Bench contains 26K annotated QA instances with eight reflective-memory dimensions and three task formats, requiring models to move beyond surface-level retrieval and infer latent meanings from evidence distributed across interaction histories. To enhance reflective memory capability, we propose REflective Memory INDuction (REMIND), a hierarchical framework that treats reflective memory as progressive meaning construction. REMIND couples question-conditioned evidence retrieval, salience-aware grounding, and abstraction-level supervision, and uses Progressive Reflective Alignment to distill high-level reflective reasoning into the factual inference pathway. Experiments show RefMem-Bench poses a substantial challenge to current models, while REMIND consistently improves both answer accuracy and memory recall through progressive evidence perception, grounding, and abstraction.

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Latest papers 193