Papers by María Andrea Cruz Blandón
MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation (2025.acl-long)
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María Andrea Cruz Blandón, Jayasimha Talur, Bruno Charron, Dong Liu, Saab Mansour, Marcello Federico
| Challenge: | Existing benchmarks focus on English or use translated data, which fails to capture cultural nuances. |
| Approach: | They propose to use a multilingual end-to-end Meta-Evaluation RAG benchmark MEMERAG to assess accuracy and faithfulness of RAG systems. |
| Outcome: | The proposed benchmark can identify improvements offered by advanced prompting techniques and LLMs. |