AnnoRetrieve uses auto-generated structured schemas and queries to retrieve information from unstructured documents more efficiently and accurately than embedding-based methods.
MEB ench: Benchmarking Large Language Models for Cross-Document Multi-Entity Question Answering
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KnowledgeBerg benchmark shows open-source LLMs achieve only 5.26-36.88 F1 on universe enumeration and 16-44% accuracy on knowledge-grounded compositional reasoning, with persistent failures in completeness, awareness, and application.
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AnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis
AnnoRetrieve uses auto-generated structured schemas and queries to retrieve information from unstructured documents more efficiently and accurately than embedding-based methods.
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KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models
KnowledgeBerg benchmark shows open-source LLMs achieve only 5.26-36.88 F1 on universe enumeration and 16-44% accuracy on knowledge-grounded compositional reasoning, with persistent failures in completeness, awareness, and application.