Search Results for author: Adrià De Gispert

Found 9 papers, 1 papers with code

Strong and Efficient Baselines for Open Domain Conversational Question Answering

no code implementations23 Oct 2023 Andrei C. Coman, Gianni Barlacchi, Adrià De Gispert

Unlike the Open Domain Question Answering (ODQA) setting, the conversational (ODConvQA) domain has received limited attention when it comes to reevaluating baselines for both efficiency and effectiveness.

Conversational Question Answering Open-Domain Question Answering +2

xPQA: Cross-Lingual Product Question Answering across 12 Languages

1 code implementation16 May 2023 Xiaoyu Shen, Akari Asai, Bill Byrne, Adrià De Gispert

To study this practical industrial task, we present xPQA, a large-scale annotated cross-lingual PQA dataset in 12 languages across 9 branches, and report results in (1) candidate ranking, to select the best English candidate containing the information to answer a non-English question; and (2) answer generation, to generate a natural-sounding non-English answer based on the selected English candidate.

Answer Generation Machine Translation +3

Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey

no code implementations5 Aug 2022 Xiaoyu Shen, Svitlana Vakulenko, Marco del Tredici, Gianni Barlacchi, Bill Byrne, Adrià De Gispert

Dense retrieval (DR) approaches based on powerful pre-trained language models (PLMs) achieved significant advances and have become a key component for modern open-domain question-answering systems.

Open-Domain Question Answering Retrieval

Neural Machine Translation Decoding with Terminology Constraints

no code implementations NAACL 2018 Eva Hasler, Adrià De Gispert, Gonzalo Iglesias, Bill Byrne

Despite the impressive quality improvements yielded by neural machine translation (NMT) systems, controlling their translation output to adhere to user-provided terminology constraints remains an open problem.

Machine Translation NMT +1

Accelerating NMT Batched Beam Decoding with LMBR Posteriors for Deployment

no code implementations NAACL 2018 Gonzalo Iglesias, William Tambellini, Adrià De Gispert, Eva Hasler, Bill Byrne

We describe a batched beam decoding algorithm for NMT with LMBR n-gram posteriors, showing that LMBR techniques still yield gains on top of the best recently reported results with Transformers.


Neural Machine Translation by Minimising the Bayes-risk with Respect to Syntactic Translation Lattices

no code implementations EACL 2017 Felix Stahlberg, Adrià De Gispert, Eva Hasler, Bill Byrne

This makes our approach much more flexible than $n$-best list or lattice rescoring as the neural decoder is not restricted to the SMT search space.

Machine Translation NMT +1

Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization

no code implementations NAACL 2016 Daniel Beck, Adrià De Gispert, Gonzalo Iglesias, Aurelien Waite, Bill Byrne

We address the problem of automatically finding the parameters of a statistical machine translation system that maximize BLEU scores while ensuring that decoding speed exceeds a minimum value.

Bayesian Optimization Machine Translation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.