Elephantasm

RESEARCH ARCHIVE
3 DOCUMENTS
RESEARCH LIBRARY
A curated collection of research papers, whitepapers, and technical guides exploring Long-Term Agentic Memory (LTAM), AI agents, and memory systems. Includes both Elephantasm publications and relevant third-party research.
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report·2025-11-04
Training Proactive and Personalized LLM Agents

Training Proactive and Personalized LLM Agents

Sun et al. introduce PPP-Agent, a reinforcement learning framework that optimizes LLM agents for productivity, proactivity, and personalization via th...
Weiwei Sun et al. (arXiv:2511.02208)
Original source: arxiv.org
2.1 MB
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whitepaper·2025-10-25
A Guide to Memory in Agents

A Guide to Memory in Agents

A comprehensive exploration of Long-Term Agentic Memory (LTAM)—the structured cognitive substrate that gives AI agents continuity, self-awareness, and...
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Elephantasm Team
5.9 MB
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report·2025-10-08
MemoryR1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning

MemoryR1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning

This paper presents MemoryR1, a novel approach that enhances LLM agents with the ability to manage and utilize memories through reinforcement learning...
Sikuan Yan et al. (arXiv:2508.19828)
Original source: arxiv.org
2.8 MB
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About This Collection

This research library includes both original Elephantasm publications and curated third-party research relevant to Long-Term Agentic Memory (LTAM) and AI agent systems.

External research papers are properly attributed to their original sources and link back to the original publication when available.