1 code implementation • EMNLP (MRQA) 2021 • Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans
In this paper, we present the first multilingual FAQ dataset publicly available.
1 code implementation • COLING 2022 • Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans
Automatic evaluation of open-domain dialogs remains an unsolved problem.
1 code implementation • 2 Aug 2021 • Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans
While powerful and efficient retrieval-based models exist for English, it is rarely the case for other languages for which the same amount of training data is not available.
no code implementations • EMNLP (NLP4ConvAI) 2021 • Ehsan Lotfi, Maxime De Bruyn, Jeska Buhmann, Walter Daelemans
In this work we study the unsupervised selection abilities of pre-trained generative models (e. g. BART) and show that by adding a score-and-aggregate module between encoder and decoder, they are capable of learning to pick the proper knowledge through minimising the language modelling loss (i. e. without having access to knowledge labels).
no code implementations • COLING 2022 • Jeska Buhmann, Maxime De Bruyn, Ehsan Lotfi, Walter Daelemans
In addition, we show that large groups of semantically similar questions are important for obtaining well-performing intent classification models.
no code implementations • 14 Jan 2024 • Ehsan Lotfi, Maxime De Bruyn, Jeska Buhmann, Walter Daelemans
The new wave of Large Language Models (LLM) has offered an efficient tool to curate sizeable conversational datasets.