Vid Kocijan : Publications

Journal papers

• [1]

  Pre−training and Diagnosing Knowledge Base Completion Models

  Vid Kocijan‚ Myeongjun Jang and Thomas Lukasiewicz

  In Artificial Intelligence. Vol. 329. No. 104081. April, 2024.

  Details about Pre−training and Diagnosing Knowledge Base Completion Models | BibTeX data for Pre−training and Diagnosing Knowledge Base Completion Models | Link to Pre−training and Diagnosing Knowledge Base Completion Models

• [2]

  The Defeat of the Winograd Schema Challenge

  Vid Kocijan‚ Ernest Davis‚ Thomas Lukasiewicz‚ Gary Marcus and Leora Morgenstern

  In Artificial Intelligence. Vol. 325. No. 103971. December, 2023.

  Details about The Defeat of the Winograd Schema Challenge | BibTeX data for The Defeat of the Winograd Schema Challenge | Link to The Defeat of the Winograd Schema Challenge

Conference papers

• [1]

  Counter−GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns

  Zhongbin Xie‚ Vid Kocijan‚ Thomas Lukasiewicz and Oana−Maria Camburu

  In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics‚ EACL 2023‚ Dubrovnik‚ Croatia‚ 2–6 May 2023. Pages 3761–3773. Association for Computational Linguistics. May, 2023.

  Details about Counter−GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns | BibTeX data for Counter−GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns | Link to Counter−GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns

• [2]

  Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup

  Yordan Yordanov‚ Vid Kocijan‚ Thomas Lukasiewicz and Oana−Maria Camburu

  In Findings of EMNLP 2022. Pages 3486–3501. Association for Computational Linguistics. December, 2022.

  Details about Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup | BibTeX data for Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup | Link to Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup

• [3]

  Knowledge Base Completion Meets Transfer Learning

  Vid Kocijan and Thomas Lukasiewicz

  In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2021‚ Online and in the Barceló Bávaro Convention Centre‚ Punta Cana‚ Dominican Republic‚ November 7–11‚ 2021. November, 2021.

  Details about Knowledge Base Completion Meets Transfer Learning | BibTeX data for Knowledge Base Completion Meets Transfer Learning | Link to Knowledge Base Completion Meets Transfer Learning

• [4]

  The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets

  Vid Kocijan‚ Oana−Maria Camburu and Thomas Lukasiewicz

  In Kevin Leyton−Brown and Mausam, editors, Proceedings of the 35th AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Virtual Conference‚ February 2–9‚ 2021. AAAI Press. 2021.

  Details about The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets | BibTeX data for The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets | Link to The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets

• [5]

  Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution

  Yordan Yordanov‚ Oana−Maria Camburu‚ Vid Kocijan and Thomas Lukasiewicz

  In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2020‚ November 16–20‚ 2020. Pages 4963–4969. Association for Computational Linguistics. November, 2020.

  Details about Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution | BibTeX data for Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution | Link to Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution

• [6]

  Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction

  Patrick Hohenecker‚ Frank Mtumbuka‚ Vid Kocijan and Thomas Lukasiewicz

  In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2020‚ November 16–20‚ 2020. Pages 8554–8565. Association for Computational Linguistics. November, 2020.

  Details about Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction | BibTeX data for Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction | Link to Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction

• [7]

  WikiCREM: A Large Unsupervised Corpus for Co−Reference Resolution

  Vid Kocijan‚ Oana−Maria Camburu‚ Ana−Maria Cretu‚ Yordan Yordanov‚ Phil Blunsom and Thomas Lukasiewicz

  In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing‚ EMNLP−IJCNLP 2019‚ Hong Kong‚ China‚ November 3–7‚ 2019. November, 2019.

  Details about WikiCREM: A Large Unsupervised Corpus for Co−Reference Resolution | BibTeX data for WikiCREM: A Large Unsupervised Corpus for Co−Reference Resolution | Link to WikiCREM: A Large Unsupervised Corpus for Co−Reference Resolution

• [8]

  A Surprisingly Robust Trick for the Winograd Schema Challenge

  Vid Kocijan‚ Ana−Maria Cretu‚ Oana−Maria Camburu‚ Yordan Yordanov and Thomas Lukasiewicz

  In Anna Korhonen and David Traum, editors, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics‚ ACL 2019‚ Florence‚ Italy‚ July 28 − August 2‚ 2019. Association for Computational Linguistics. July, 2019.

  Details about A Surprisingly Robust Trick for the Winograd Schema Challenge | BibTeX data for A Surprisingly Robust Trick for the Winograd Schema Challenge | Link to A Surprisingly Robust Trick for the Winograd Schema Challenge