Veselin Stoyanov

Publications
Influence

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Y. Liu, Myle Ott, +7 authors Veselin Stoyanov
Computer Science
ArXiv
26 July 2019

We present a replication study of BERT pretraining (Devlin et al., 2019) that carefully measures the impact of many key hyperparameters and training data size. Expand

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Unsupervised Cross-lingual Representation Learning at Scale

Alexis Conneau, Kartikay Khandelwal, +7 authors Veselin Stoyanov
Computer Science
ACL
5 November 2019

We present XLM-R a transformer-based multilingual masked language model pre-trained on one hundred languages, which obtains state-of-the-art performance on cross-lingual classification, sequence labeling and question answering. Expand

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

M. Lewis, Yinhan Liu, +5 authors Luke Zettlemoyer
Computer Science, Mathematics
ACL
29 October 2019

We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. Expand

XNLI: Evaluating Cross-lingual Sentence Representations

Alexis Conneau, Guillaume Lample, +4 authors Veselin Stoyanov
Computer Science
EMNLP
13 September 2018

We extend the Multi-Genre Natural Language Inference Corpus (MultiNLI) to 14 languages, including low-resource languages such as Swahili and Urdu. Expand

SemEval-2013 Task 2: Sentiment Analysis in Twitter

Preslav Nakov, Alan Ritter, Sara Rosenthal, F. Sebastiani, Veselin Stoyanov
Computer Science
SemEval@NAACL-HLT
1 June 2013

We have proposed SemEval-2013 Task 2: Sentiment Analysis in Twitter, which included two subtasks: A, an expression-level subtask, and B, a message level subtask. Expand

SemEval-2017 Task 4: Sentiment Analysis in Twitter

Preslav Nakov, Alan Ritter, Sara Rosenthal, F. Sebastiani, Veselin Stoyanov
Computer Science
NAACL
1 June 2016

This paper discusses the fourth year of the ”Sentiment Analysis in Twitter Task” task at SemEval and introduces a new language, Arabic. Expand

SemEval-2015 Task 10: Sentiment Analysis in Twitter

Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M. Mohammad, Alan Ritter, Veselin Stoyanov
Computer Science
SemEval@NAACL-HLT
1 June 2015

In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter. Expand

SemEval-2014 Task 9: Sentiment Analysis in Twitter

Sara Rosenthal, Alan Ritter, Preslav Nakov, Veselin Stoyanov
Computer Science
COLING
1 August 2014

We describe the Sentiment Analysis in Twitter task, ran as part of SemEval-2014. Expand

Conundrums in Noun Phrase Coreference Resolution: Making Sense of the State-of-the-Art

Veselin Stoyanov, Nathan Gilbert, Claire Cardie, E. Riloff
Computer Science
ACL/IJCNLP
2 August 2009

We aim to shed light on the state-of-the-art in NP coreference resolution by teasing apart the differences in the MUC and ACE task definitions, the assumptions made in evaluation methodologies, and inherent differences in text corpora. Expand

Evaluation Measures for the SemEval-2016 Task 4 “Sentiment Analysis in Twitter” (Draft: Version 1.13)

Preslav Nakov, Alan Ritter, Sara Rosenthal, F. Sebastiani, Veselin Stoyanov
2016

This informal document details the evaluation measures that will be used in SemEval2016 Task 4 “Sentiment Analysis in Twitter”, a revamped edition of SemEval-2015 Task 10 (Rosenthal et al., 2015).… Expand

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