4 papers
Datasets for Multilingual Answer Sentence Selection
Matteo Gabburo, Stefano Campese, Federico Agostini +1
Answer Sentence Selection (AS2) is a critical task for designing effective retrieval-based Question Answering (QA) systems. Most advancements in AS2 focus on English due to the sca…
Measuring Retrieval Complexity in Question Answering Systems
Matteo Gabburo, Nicolaas Paul Jedema, Siddhant Garg +2
In this paper, we investigate which questions are challenging for retrieval-based Question Answering (QA). We (i) propose retrieval complexity (RC), a novel metric conditioned on t…
SQUARE: Automatic Question Answering Evaluation using Multiple Positive and Negative References
Matteo Gabburo, Siddhant Garg, Rik Koncel Kedziorski +1
Evaluation of QA systems is very challenging and expensive, with the most reliable approach being human annotations of correctness of answers for questions. Recent works (AVA, BEM)…
Learning Answer Generation using Supervision from Automatic Question Answering Evaluators
Matteo Gabburo, Siddhant Garg, Rik Koncel-Kedziorski +1
Recent studies show that sentence-level extractive QA, i.e., based on Answer Sentence Selection (AS2), is outperformed by Generation-based QA (GenQA) models, which generate answers…