Search Results for author: Goran Glava{\v{s}}

Found 42 papers, 5 papers with code

From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers

no code implementations EMNLP 2020 Anne Lauscher, Vinit Ravishankar, Ivan Vuli{\'c}, Goran Glava{\v{s}}

Massively multilingual transformers (MMTs) pretrained via language modeling (e. g., mBERT, XLM-R) have become a default paradigm for zero-shot language transfer in NLP, offering unmatched transfer performance.

Cross-Lingual Word Embeddings Dependency Parsing +4

LexFit: Lexical Fine-Tuning of Pretrained Language Models

no code implementations ACL 2021 Ivan Vuli{\'c}, Edoardo Maria Ponti, Anna Korhonen, Goran Glava{\v{s}}

Inspired by prior work on semantic specialization of static word embedding (WE) models, we show that it is possible to expose and enrich lexical knowledge from the LMs, that is, to specialize them to serve as effective and universal {``}decontextualized{''} word encoders even when fed input words {``}in isolation{''} (i. e., without any context).

Cross-Lingual Transfer Pretrained Language Models

SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment

no code implementations SEMEVAL 2020 Goran Glava{\v{s}}, Ivan Vuli{\'c}, Anna Korhonen, Simone Paolo Ponzetto

The shared task spans three dimensions: (1) monolingual vs. cross-lingual LE, (2) binary vs. graded LE, and (3) a set of 6 diverse languages (and 15 corresponding language pairs).

Lexical Entailment Natural Language Inference

Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces

no code implementations WS 2020 Ivan Vuli{\'c}, Anna Korhonen, Goran Glava{\v{s}}

Work on projection-based induction of cross-lingual word embedding spaces (CLWEs) predominantly focuses on the improvement of the projection (i. e., mapping) mechanisms.

Bilingual Lexicon Induction

Cross-lingual Semantic Specialization via Lexical Relation Induction

no code implementations IJCNLP 2019 Edoardo Maria Ponti, Ivan Vuli{\'c}, Goran Glava{\v{s}}, Roi Reichart, Anna Korhonen

Semantic specialization integrates structured linguistic knowledge from external resources (such as lexical relations in WordNet) into pretrained distributional vectors in the form of constraints.

Lexical Simplification Semantic Textual Similarity +2

Specializing Distributional Vectors of All Words for Lexical Entailment

no code implementations WS 2019 Aishwarya Kamath, Jonas Pfeiffer, Edoardo Maria Ponti, Goran Glava{\v{s}}, Ivan Vuli{\'c}

Semantic specialization methods fine-tune distributional word vectors using lexical knowledge from external resources (e. g. WordNet) to accentuate a particular relation between words.

Cross-Lingual Transfer Lexical Entailment +2

Computational Analysis of Political Texts: Bridging Research Efforts Across Communities

no code implementations ACL 2019 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

Political scientists created resources and used available NLP methods to process textual data largely in isolation from the NLP community.

Stance Detection

Multilingual and Cross-Lingual Graded Lexical Entailment

no code implementations ACL 2019 Ivan Vuli{\'c}, Simone Paolo Ponzetto, Goran Glava{\v{s}}

Starting from HyperLex, the only available GR-LE dataset in English, we construct new monolingual GR-LE datasets for three other languages, and combine those to create a set of six cross-lingual GR-LE datasets termed CL-HYPERLEX.

Lexical Entailment

Generalized Tuning of Distributional Word Vectors for Monolingual and Cross-Lingual Lexical Entailment

1 code implementation ACL 2019 Goran Glava{\v{s}}, Ivan Vuli{\'c}

Lexical entailment (LE; also known as hyponymy-hypernymy or is-a relation) is a core asymmetric lexical relation that supports tasks like taxonomy induction and text generation.

Lexical Entailment Text Generation

An Argument-Annotated Corpus of Scientific Publications

no code implementations WS 2018 Anne Lauscher, Goran Glava{\v{s}}, Simone Paolo Ponzetto

We analyze the annotated argumentative structures and investigate the relations between argumentation and other rhetorical aspects of scientific writing, such as discourse roles and citation contexts.

Argument Mining

Explicit Retrofitting of Distributional Word Vectors

no code implementations ACL 2018 Goran Glava{\v{s}}, Ivan Vuli{\'c}

The ER model allows us to learn a global specialization function and specialize the vectors of words unobserved in the training data as well.

Lexical Simplification Semantic Textual Similarity +2

Discriminating between Lexico-Semantic Relations with the Specialization Tensor Model

1 code implementation NAACL 2018 Goran Glava{\v{s}}, Ivan Vuli{\'c}

We present a simple and effective feed-forward neural architecture for discriminating between lexico-semantic relations (synonymy, antonymy, hypernymy, and meronymy).

Natural Language Inference Paraphrase Generation +2

Cross-Lingual Classification of Topics in Political Texts

no code implementations WS 2017 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

In this paper, we propose an approach for cross-lingual topical coding of sentences from electoral manifestos of political parties in different languages.

General Classification Text Classification +2

Unsupervised Cross-Lingual Scaling of Political Texts

1 code implementation EACL 2017 Goran Glava{\v{s}}, Federico Nanni, Simone Paolo Ponzetto

Political text scaling aims to linearly order parties and politicians across political dimensions (e. g., left-to-right ideology) based on textual content (e. g., politician speeches or party manifestos).

Improving Neural Knowledge Base Completion with Cross-Lingual Projections

no code implementations EACL 2017 Patrick Klein, Simone Paolo Ponzetto, Goran Glava{\v{s}}

We exploit multilingual synsets from BabelNet to translate English triples to other languages and then augment the reference knowledge base with cross-lingual triples.

Knowledge Base Completion Link Prediction +2

Cannot find the paper you are looking for? You can Submit a new open access paper.