Memory Type Varies: Empowering LLM Agents for Long-Term Memory with Diverse Strategies
cs.AI
Submitted: 2026-10-08
Updated: 2026-10-08
Comments: NeurIPS 2026 Accept Paper
Code: https://github.com/wenyiwy99/MemoType
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Keep Me Updated! Memory Management in Long-term Conversations
- Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- From Local to Global: A Graph RAG Approach to Query-Focused Summarization
- LightMem: Lightweight and Efficient Memory-Augmented Generation
- Memp: Exploring Agent Procedural Memory
- From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
- Memory in the Age of AI Agents
- GPT-4o System Card
- Unsupervised Dense Information Retrieval with Contrastive Learning
- Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale
- PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
- Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs
- Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
- MemOS: A Memory OS for AI System
- Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory
- PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments
- MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
- What Deserves Memory: Adaptive Memory Distillation for LLM Agents
- MemGPT: Towards LLMs as Operating Systems
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