ESL-Bench supplies 100 synthetic user trajectories and 10,000 queries showing database agents achieve 48-58% accuracy while memory RAG baselines reach only 30-38% on longitudinal health reasoning.
A survey of graph retrieval-augmented generation for customized large language models
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Graph RAG that embeds structural and lexical features from ETSI standards improves retrieval performance over vanilla vector methods on a custom Q&A dataset.
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ESL-Bench: An Event-Driven Synthetic Longitudinal Benchmark for Health Agents
ESL-Bench supplies 100 synthetic user trajectories and 10,000 queries showing database agents achieve 48-58% accuracy while memory RAG baselines reach only 30-38% on longitudinal health reasoning.
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Exploring Structural Complexity in Normative RAG with Graph-based approaches: A case study on the ETSI Standards
Graph RAG that embeds structural and lexical features from ETSI standards improves retrieval performance over vanilla vector methods on a custom Q&A dataset.