Introduces a 93-question multimodal RAG benchmark with phrase-level recall and embedding-based hallucination metrics, finding closed-source pipelines outperform open-source ones especially on cross-modal and cross-document tasks.
Rbench: Graduate-level multi- disciplinary benchmarks for llm & mllm complex reasoning evaluation,
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FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation
Introduces a 93-question multimodal RAG benchmark with phrase-level recall and embedding-based hallucination metrics, finding closed-source pipelines outperform open-source ones especially on cross-modal and cross-document tasks.