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 • 8 Nov 2015 • Ehsan Lotfi
The ozone level prediction is an important task of air quality agencies of modern cities.
no code implementations • WS 2020 • Jens Lemmens, Ben Burtenshaw, Ehsan Lotfi, Ilia Markov, Walter Daelemans
We present an ensemble approach for the detection of sarcasm in Reddit and Twitter responses in the context of The Second Workshop on Figurative Language Processing held in conjunction with ACL 2020.
no code implementations • COLING 2020 • Ehsan Lotfi, Ilia Markov, Walter Daelemans
Native language identification (NLI) {--} identifying the native language (L1) of a person based on his/her writing in the second language (L2) {--} is useful for a variety of purposes, including marketing, security, and educational applications.
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.