Learning What to Share and What to Personalize: Hierarchical Strategy Co-Evolution for Agent Memory
cs.AI, cs.CL
Submitted: 2026-08-26
Updated: 2026-08-26
Code: https://github.com/Hyp26cs/HiPS
Terminology
Sources
- Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
- LightMem: Lightweight and Efficient Memory-Augmented Generation
- EverMemOS: A Self-Organizing Memory Operating System for Structured Long-Horizon Reasoning
- Memory in the Age of AI Agents
- Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale
- MemOS: An Operating System for Memory-Augmented Generation (MAG) in Large Language Models
- PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments
- MemGPT: Towards LLMs as Operating Systems
- Qwen2.5 Technical Report
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents
- Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL
- MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
- Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory
- Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
- MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents
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