LoCoMo
Emerging32papers using it
187HF downloads
3HF likes
2025first seen
LoCoMo is a dataset/benchmark used to evaluate the performance of memory-augmented language model agents in long-horizon interactions.
Papers using LoCoMo (32)
- 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 MemoryAtomMem: Building Simple and Effective Memory System for LLM Agents via Atomic FactsMnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM MemoryMemory Shot for Long-Term DialogueMGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue AgentsMemMachine: A Ground-Truth-Preserving Memory System for Personalized AI AgentsHierarchical Memory for High-Efficiency Long-Term Reasoning in LLM AgentsMIRIX: Multi-Agent Memory System for LLM-Based AgentsRethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent MemoryEvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic EnvironmentsLocas: Your Models are Principled Initializers of Locally-Supported Parametric MemoriesLearning Query-Aware Budget-Tier Routing for Runtime Agent MemoryQuery-focused and Memory-aware Reranker for Long Context ProcessingMemMA: Coordinating the Memory Cycle through Multi-Agent Reasoning and In-Situ Self-EvolutionΞ΄-mem: Efficient Online Memory for Large Language ModelsMemForest: An Efficient Agent Memory System with Hierarchical Temporal IndexingMemory Matters More: Event-Centric Memory as a Logic Map for Agent Searching and ReasoningAdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue AgentsEvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM AgentsWhen Classic Cache Policies Fail: Learning-Augmented Replacement for Semantic Retrieval BuffersGAM: 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 AgentsMemLoRA: Distilling Expert Adapters for On-Device Memory Systems