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D-Index & Metrics

Computer Science

D-Index
32
Citations
28266
World Ranking
12830
National Ranking
5168

Overview

Veselin Stoyanov is affiliated with Facebook in the United States and has contributed extensively to the field of computer science with a particular focus on artificial intelligence. Their research spans multiple domains including topic modeling, multimodal machine learning applications, and natural language processing techniques.

Stoyanov's publication record shows a significant emphasis on addressing challenges related to domain adaptation and few-shot learning, as well as speech recognition and synthesis. Their contributions also touch on interpreting and communication in healthcare and the detection of hate speech and cyberbullying.

The scientist's recent papers include the following:

  • Towards Learning Terminological Concept Systems from Multilingual Natural Language Text, 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Few-shot Learning with Multilingual Language Models, 2021, arXiv (Cornell University)
  • Prompt-free and Efficient Few-shot Learning with Language Models, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Improving In-Context Few-Shot Learning via Self-Supervised Training, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs, 2021, arXiv (Cornell University)

Frequent coauthors involved in collaborations with Stoyanov are:

  • Jingfei Du
  • Luke Zettlemoyer
  • Ramakanth Pasunuru
  • Zornitsa Kozareva
  • Myle Ott

Stoyanov's work has appeared primarily in the following publication venues:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

The main fields of study where Stoyanov has contributed include computer science, with an emphasis on artificial intelligence and computer vision and pattern recognition. Their multidisciplinary approach integrates various technical areas to address complex computational problems involving language and multimodal data processing.

Best Publications

  • RoBERTa: A Robustly Optimized BERT Pretraining Approach

    Yinhan Liu;Myle Ott;Naman Goyal;Jingfei Du

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

    Mike Lewis;Yinhan Liu;Naman Goyal;Marjan Ghazvininejad

  • Unsupervised Cross-lingual Representation Learning at Scale

    Alexis Conneau;Kartikay Khandelwal;Naman Goyal;Vishrav Chaudhary

  • SemEval-2016 Task 4: Sentiment Analysis in Twitter

    Preslav Nakov;Alan Ritter;Sara Rosenthal;Fabrizio Sebastiani

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams

  • Unsupervised Cross-lingual Representation Learning at Scale.

    Alexis Conneau;Kartikay Khandelwal;Naman Goyal;Vishrav Chaudhary

  • SemEval-2013 Task 2: Sentiment Analysis in Twitter

    Preslav Nakov;Sara Rosenthal;Zornitsa Kozareva;Veselin Stoyanov

  • SemEval-2014 Task 9: Sentiment Analysis in Twitter

    Sara Rosenthal;Alan Ritter;Preslav Nakov;Veselin Stoyanov

  • SemEval-2015 Task 10: Sentiment Analysis in Twitter

    Sara Rosenthal;Preslav Nakov;Svetlana Kiritchenko;Saif Mohammad

  • System and method for automatically summarizing fine-grained opinions in digital text

    Claire Cardie;Veselin Stoyanov;Yejin Choi;Eric Breck

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Guillaume Lample;Ruty Rinott;Adina Williams

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Alexis Conneau;Shijie Wu;Haoran Li;Luke Zettlemoyer

  • Few-shot Learning with Multilingual Generative Language Models

    Unknown

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

    Veselin Stoyanov;Nathan Gilbert;Claire Cardie;Ellen Riloff

  • Topic Identification for Fine-Grained Opinion Analysis

    Veselin Stoyanov;Claire Cardie

  • Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model

    Wenhan Xiong;Jingfei Du;William Yang Wang;Veselin Stoyanov

  • Multi-Perspective Question Answering Using the OpQA Corpus

    Veselin Stoyanov;Claire Cardie;Janyce Wiebe

  • Efficient Large Scale Language Modeling with Mixtures of Experts

    Unknown

  • Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art.

    Patrick S. H. Lewis;Myle Ott;Jingfei Du;Veselin Stoyanov

  • Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure

    Veselin Stoyanov;Alexander Ropson;Jason Eisner

  • Self-training Improves Pre-training for Natural Language Understanding

    Jingfei Du;Edouard Grave;Beliz Gunel;Vishrav Chaudhary

  • Coreference Resolution with Reconcile

    Veselin Stoyanov;Claire Cardie;Nathan Gilbert;Ellen Riloff

  • A multi-lingual multi-task architecture for low-resource sequence labeling

    Ying Lin;Shengqi Yang;Veselin Stoyanov;Heng Ji

  • Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts

    Preslav Nakov;Sara Rosenthal;Svetlana Kiritchenko;Saif M. Mohammad

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Shijie Wu;Alexis Conneau;Haoran Li;Luke Zettlemoyer

  • SemEval-2015 Task 10: Sentiment Analysis in Twitter

    Sara Rosenthal;Saif M Mohammad;Preslav Nakov;Alan Ritter

  • SemEval-2013 Task 2: Sentiment Analysis in Twitter

    Preslav Nakov;Zornitsa Kozareva;Alan Ritter;Sara Rosenthal

  • SemEval-2014 Task 9: Sentiment Analysis in Twitter

    Sara Rosenthal;Preslav Nakov;Alan Ritter;Veselin Stoyanov

Frequent Co-Authors

Claire Cardie
Claire Cardie Cornell University
Alexis Conneau
Alexis Conneau Facebook (United States)
Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Alan Ritter
Alan Ritter Georgia Institute of Technology
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Myle Ott
Myle Ott Facebook (United States)
Michael Lewis
Michael Lewis University of Pittsburgh
Edouard Grave
Edouard Grave Facebook (United States)
Ellen Riloff
Ellen Riloff University of Utah
Janyce Wiebe
Janyce Wiebe University of Pittsburgh

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