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Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ...
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RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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Verb Knowledge Injection for Multilingual Event Processing ...
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Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
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Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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Training and domain adaptation for supervised text segmentation
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XHate-999: Analyzing and Detecting Abusive Language Across Domains and Languages ...
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From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
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XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
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Verb Knowledge Injection for Multilingual Event Processing ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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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 ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://dx.doi.org/10.48448/2p49-kh89 https://underline.io/lecture/6409-semeval-2020-task-2-predicting-multilingual-and-cross-lingual-(graded)-lexical-entailment
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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Non-Linear Instance-Based Cross-Lingual Mapping for Non-Isomorphic Embedding Spaces ...
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Probing Pretrained Language Models for Lexical Semantics ...
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Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction ...
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Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces ...
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