53 articles tagged with #memory-systems. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers have developed REMem, a new framework that enables AI language agents to form and reason with episodic memory similar to humans. The system uses a two-phase approach with offline memory graph indexing and online agentic retrieval, showing significant improvements over existing memory systems like Mem0 and HippoRAG 2.
Researchers introduce AMA-Bench, a new benchmark for evaluating long-horizon memory in AI agents deployed in real-world applications. The study reveals existing memory systems underperform due to lack of causality and objective information, while their proposed AMA-Agent system achieves 57.22% accuracy, surpassing baselines by 11.16%.
Researchers present a unified framework for probabilistic AI computation that treats deterministic and stochastic data access under a common perspective. The study identifies memory systems as performance bottlenecks in trustworthy AI and proposes compute-in-memory approaches to address scalability challenges.
