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1
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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2
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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3
Verb Knowledge Injection for Multilingual Event Processing ...
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4
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
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5
Verb Knowledge Injection for Multilingual Event Processing ...
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6
Probing Pretrained Language Models for Lexical Semantics ...
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7
SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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8
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
Abstract: Unsupervised pretraining models have been shown to facilitate a wide range of downstream NLP applications. These models, however, retain some of the limitations of traditional static word embeddings. In particular, they encode only the distributional knowledge available in raw text corpora, incorporated through language modeling objectives. In this work, we complement such distributional knowledge with external lexical knowledge, that is, we integrate the discrete knowledge on word-level semantic similarity into pretraining. To this end, we generalize the standard BERT model to a multi-task learning setting where we couple BERT’s masked language modeling and next sentence prediction objectives with an auxiliary task of binary word relation classification. Our experiments suggest that our “Lexically Informed” BERT (LIBERT), specialized for the word-level semantic similarity, yields better performance than the lexically blind “vanilla” BERT on several language understanding tasks. Concretely, LIBERT ...
Keyword: Computer and Information Science; Natural Language Processing; Neural Network
URL: https://dx.doi.org/10.48448/j696-8h54
https://underline.io/lecture/6311-specializing-unsupervised-pretraining-models-for-word-level-semantic-similarity
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9
Specializing unsupervised pretraining models for word-level semantic similarity
Ponti, Edoardo Maria; Korhonen, Anna; Vulić, Ivan. - : Association for Computational Linguistics, ACL, 2020
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10
Classification-based self-learning for weakly supervised bilingual lexicon induction
Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020
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11
Probing pretrained language models for lexical semantics
Vulić, Ivan; Korhonen, Anna; Litschko, Robert. - : Association for Computational Linguistics, 2020
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12
XCOPA: A multilingual dataset for causal commonsense reasoning
Ponti, Edoardo Maria; Majewska, Olga; Liu, Qianchu. - : Association for Computational Linguistics, 2020
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13
Improving bilingual lexicon induction with unsupervised post-processing of monolingual word vector spaces
Glavaš, Goran; Korhonen, Anna; Vulić, Ivan. - : 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
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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16
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ...
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17
Multilingual and cross-lingual graded lexical entailment
Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019
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18
How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019
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19
Cross-lingual semantic specialization via lexical relation induction
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019
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20
Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment
Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019
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