LoCoMo
Emerging26papers using it
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LoCoMo is a dataset/benchmark used to evaluate the performance of memory-augmented LLM agents in long-horizon interactions.
Papers using LoCoMo (25)
- Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement LearningEpiCache: Episodic KV Cache Management for Long-Term Conversation on Resource-Constrained EnvironmentsMem0: Building Production-Ready AI Agents with Scalable Long-Term MemoryMnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM MemoryMGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue AgentsMemMachine: A Ground-Truth-Preserving Memory System for Personalized AI AgentsRethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent MemoryMemMA: Coordinating the Memory Cycle through Multi-Agent Reasoning and In-Situ Self-EvolutionΞ΄-mem: Efficient Online Memory for Large Language ModelsLocas: Your Models are Principled Initializers of Locally-Supported Parametric MemoriesQuery-focused and Memory-aware Reranker for Long Context ProcessingEvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM AgentsMemForest: An Efficient Agent Memory System with Hierarchical Temporal IndexingGAM: Hierarchical Graph-based Agentic Memory for LLM AgentsCooperative Memory Paging with Keyword Bookmarks for Long-Horizon LLM ConversationsMemori: A Persistent Memory Layer for Efficient, Context-Aware LLM AgentsDeveloping Adaptive Context Compression Techniques for Large Language Models (LLMs) in Long-Running InteractionsMemSkill: Learning and Evolving Memory Skills for Self-Evolving AgentsBeyond Dialogue Time: Temporal Semantic Memory for Personalized LLM AgentsDYCP: Dynamic Context Pruning for Long-Form Dialogue with LLMsE-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent MemoryMemR$^3$: Memory Retrieval via Reflective Reasoning for LLM AgentsHierarchical Memory for High-Efficiency Long-Term Reasoning in LLM AgentsMIRIX: Multi-Agent Memory System for LLM-Based AgentsMemLoRA: Distilling Expert Adapters for On-Device Memory Systems