arXiv AI
Interactive Memory Learning for Long-Term Conversations
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AdMem: Advanced Memory for Task-solving Agents
arXiv:2606. 06787v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise as tool-using agents but remain limited in long-horizon tasks that require remembering, organizing, and reusing knowledge.
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arXiv AI
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Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
arXiv:2507. 05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while another critical component-memory, encompassing how agents memorize, update, and retrieve long-term information-is under-evaluated due to the lack of benchmarks.
arXiv AI
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ThinkFlow: Self-Evolving Probabilistic Latent Memory for Lifelong Conversational Agents
arXiv:2609.17010v1 Announce Type: new Abstract: Lifelong conversational agents rely on memory systems to maintain deep, context-aware interactions with users. However, existing explicit textual memor...
arXiv AI
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AMBER: Training Long-Horizon Web Agents through Append-Only Memory
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