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1
On cross-lingual retrieval with multilingual text encoders
Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer Science + Business Media, 2022
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2
On Cross-Lingual Retrieval with Multilingual Text Encoders ...
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3
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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4
Come hither or go away? Recognising pre-electoral coalition signals in the news ...
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5
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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6
Come hither or go away? Recognising pre-electoral coalition signals in the news
Rehbein, Ines; Ponzetto, Simone Paolo; Adendorf, Anna. - : Association for Computational Linguistics, 2021
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AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ...
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8
Word Sense Disambiguation for 158 Languages using Word Embeddings Only ...
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9
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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10
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena; Ponzetto, Simone Paolo. - : Apollo - University of Cambridge Repository, 2020
Abstract: Lexical entailment (LE) is a fundamental asymmetric lexico-semantic relation, supporting the hierarchies in lexical resources (e.g., WordNet, ConceptNet) and applications like natural language inference and taxonomy induction. Multilingual and cross-lingual NLP applications warrant models for LE detection that go beyond language boundaries. As part of SemEval 2020, we carried out a shared task (Task 2) on multilingual and cross-lingual LE. The shared task spans three dimensions: (1) monolingual LE in multiple languages versus cross-lingual LE, (2) binary versus graded LE, and (3) a set of 6 diverse languages (and 15 corresponding language pairs). We offered two different evaluation tracks: (a) distributional (Dist): for unsupervised, fully distributional models that capture LE solely on the basis of unannotated corpora, and (b)Any: for externally informed models, allowed to leverage any resources, including lexico-semantic networks (e.g.,WordNet or BabelNet). In the Any track, we received system runs that ...
URL: https://dx.doi.org/10.17863/cam.62204
https://www.repository.cam.ac.uk/handle/1810/315097
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11
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment
Glavas, Goran; Vulic, Ivan; Korhonen, Anna-Leena. - : International Committee for Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.semeval-1.2, 2020. : Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020), 2020
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12
A Twitter Political Corpus of the 2019 10N Spanish Election
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13
AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2020
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14
SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2020
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15
FacTweet: Profiling Fake News Twitter Accounts
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16
Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ...
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Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ...
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18
HHMM at SemEval-2019 Task 2: Unsupervised frame induction using contextualized word embeddings
Arefyev, Nikolay; Panchenko, Alexander; Anwar, Saba. - : Association for Computational Linguistics, ACL, 2019
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19
Policy preference detection in parliamentary debate motions
Abercrombie, Gavin; Ponzetto, Simone Paolo; Batista-Navarro, Riza. - : Association for Computational Linguistics, 2019
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20
Watset: Local-global graph clustering with applications in sense and frame induction
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