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1
XHate-999: analyzing and detecting abusive language across domains and languages
Glavaš, Goran [Verfasser]; Karan, Mladen [Verfasser]; Vulic, Ivan [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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2
Specializing unsupervised pretraining models for word-level semantic similarity
Lauscher, Anne [Verfasser]; Vulic, Ivan [Verfasser]; Ponti, Edoardo Maria [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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3
Towards instance-level parser selection for cross-lingual transfer of dependency parsers
Litschko, Robert [Verfasser]; Vulic, Ivan [Verfasser]; Agić, Želiko [Verfasser]. - Mannheim : Universitätsbibliothek Mannheim, 2021
DNB Subject Category Language
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4
Data for paper: "Evaluating Resource-Lean Cross-Lingual Embedding Models in Unsupervised Retrieval" ...
Litschko, Robert; Glavaš, Goran. - : Mannheim University Library, 2021
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5
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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6
On Cross-Lingual Retrieval with Multilingual Text Encoders ...
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7
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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8
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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9
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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10
Verb Knowledge Injection for Multilingual Event Processing ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.541 Abstract: Linguistic probing of pretrained Transformer-based language models (LMs) revealed that they encode a range of syntactic and semantic properties of a language. However, they are still prone to fall back on superficial cues and simple heuristics to solve downstream tasks, rather than leverage deeper linguistic information. In this paper, we target a specific facet of linguistic knowledge, the interplay between verb meaning and argument structure. We investigate whether injecting explicit information on verbs’ semantic-syntactic behaviour improves the performance of pretrained LMs in event extraction tasks, where accurate verb processing is paramount. Concretely, we impart the verb knowledge from curated lexical resources into dedicated adapter modules (verb adapters), allowing it to complement, in downstream tasks, the language knowledge obtained during LM-pretraining. We first demonstrate that injecting verb knowledge leads to performance ...
URL: https://underline.io/lecture/25772-verb-knowledge-injection-for-multilingual-event-processing
https://dx.doi.org/10.48448/cje1-ae20
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11
Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021
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12
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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13
Training and domain adaptation for supervised text segmentation
Glavaš, Goran; Ganesh, Ananya; Somasundaran, Swapna. - : Association for Computational Linguistics, 2021
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