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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification ... Spithourakis, Georgios P.; Vulić, Ivan; Lis, Michał. - : arXiv, 2022 BASE Show details 2 Improving Word Translation via Two-Stage Contrastive Learning ... Li, Yaoyiran; Liu, Fangyu; Collier, Nigel. - : arXiv, 2022 BASE Show details 3 Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 4 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... Liu, Fangyu; Vulić, Ivan; Korhonen, Anna. - : arXiv, 2021 BASE Show details 5 Emergent Communication Pretraining for Few-Shot Machine Translation ... Li, Yaoyiran; Ponti, Edoardo M.; Vulić, Ivan. - : arXiv, 2020 BASE Show details 6 On the Limitations of Unsupervised Bilingual Dictionary Induction ... Søgaard, Anders; Ruder, Sebastian; Vulić, Ivan. - : arXiv, 2018 BASE Show details 7 Fully Statistical Neural Belief Tracking ... Mrkšić, Nikola; Vulić, Ivan. - : arXiv, 2018 Abstract: This paper proposes an improvement to the existing data-driven Neural Belief Tracking (NBT) framework for Dialogue State Tracking (DST). The existing NBT model uses a hand-crafted belief state update mechanism which involves an expensive manual retuning step whenever the model is deployed to a new dialogue domain. We show that this update mechanism can be learned jointly with the semantic decoding and context modelling parts of the NBT model, eliminating the last rule-based module from this DST framework. We propose two different statistical update mechanisms and show that dialogue dynamics can be modelled with a very small number of additional model parameters. In our DST evaluation over three languages, we show that this model achieves competitive performance and provides a robust framework for building resource-light DST models. ... : Accepted as a short paper for the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018) ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.1805.11350 https://arxiv.org/abs/1805.11350 BASE Hide details 8 Scoring Lexical Entailment with a Supervised Directional Similarity Network ... Rei, Marek; Gerz, Daniela; Vulić, Ivan. - : arXiv, 2018 BASE Show details 9 A Survey Of Cross-lingual Word Embedding Models ... Ruder, Sebastian; Vulić, Ivan; Søgaard, Anders. - : arXiv, 2017 BASE Show details 10 Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ... Mrkšić, Nikola; Vulić, Ivan; Séaghdha, Diarmuid Ó. - : arXiv, 2017 BASE Show details

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