Search Results for author: Eric Lind

Found 3 papers, 0 papers with code

Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems

no code implementations15 Jan 2022 Yoshitomo Matsubara, Luca Soldaini, Eric Lind, Alessandro Moschitti

An MHS model consists of two components: a stack of transformer layers that is used to encode inputs, and a set of ranking heads; each of them is trained by distilling a different large transformer architecture.

Question Answering

Cross-Lingual GenQA: Open-Domain Question Answering with Answer Sentence Generation

no code implementations14 Oct 2021 Benjamin Muller, Luca Soldaini, Rik Koncel-Kedziorski, Eric Lind, Alessandro Moschitti

Recent approaches for question answering systems have achieved impressive performance on English by combining document-level retrieval with answer generation.

Answer Generation Generative Question Answering +1

Answer Generation for Retrieval-based Question Answering Systems

no code implementations Findings (ACL) 2021 Chao-Chun Hsu, Eric Lind, Luca Soldaini, Alessandro Moschitti

Recent advancements in transformer-based models have greatly improved the ability of Question Answering (QA) systems to provide correct answers; in particular, answer sentence selection (AS2) models, core components of retrieval-based systems, have achieved impressive results.

Answer Generation Question Answering

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