2 citations · 2 across the 3 of their papers we have counts for
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RAGferee: Building Contextual Reward Models for Retrieval-Augmented Generation
Andrei C. Coman, Ionut-Teodor Sorodoc, Leonardo F. R. Ribeiro +3
Existing Reward Models (RMs), typically trained on general preference data, struggle in Retrieval Augmented Generation (RAG) settings, which require judging responses for faithfuln…
GaRAGe: A Benchmark with Grounding Annotations for RAG Evaluation
Ionut-Teodor Sorodoc, Leonardo F. R. Ribeiro, Rexhina Blloshmi +2
We present GaRAGe, a large RAG benchmark with human-curated long-form answers and annotations of each grounding passage, allowing a fine-grained evaluation of whether LLMs can iden…
Retrieving Contextual Information for Long-Form Question Answering using Weak Supervision
Philipp Christmann, Svitlana Vakulenko, Ionut Teodor Sorodoc +2
Long-form question answering (LFQA) aims at generating in-depth answers to end-user questions, providing relevant information beyond the direct answer. However, existing retrievers…