RAGAs: Automated Evaluation of Retrieval Augmented Generation

RAGAs: автоматизированная оценка генерации с дополненной выборкой
Luis Espinosa-Anke, Shahul Es, Jithin James, Steven Schockaert
2024-01-01
SCID:  54.1/3vyhb88c Discuss with AI
RAGRAGAsautomated evaluationretrieval-augmented generation
Abstract (AI)
Shahul Es, Jithin James, Luis Espinosa Anke, Steven Schockaert. Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations. 2024.
Key Findings
1
RAGAs provides systematic evaluation capabilities for assessing retrieval and generation components in retrieval-augmented generation pipelines.
2
The available abstract metadata does not report quantitative experiments, benchmark comparisons, or specific performance results.
3
The paper presents RAGAs, an automated evaluation framework designed specifically for retrieval-augmented generation systems.
Research Object

retrieval-augmented generation (RAG) systems

Research Subject

automated evaluation of the quality and performance of retrieval-augmented generation systems

Publication Details
Publication Date
2024-01-01
Journal
Publisher
ISSN
Cited by
456
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Author Information
Authors
Luis Espinosa-Anke
Shahul Es
Jithin James
Steven Schockaert
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