Publications

Xiyuan Zou, Yiran Li, Ian Porada, Jackie Cheung (2024). Separately Parameterizing Singleton Detection Improves End-to-end Neural Coreference Resolution. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers).
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Ian Porada, Alexandra Olteanu, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung (2024). Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective. arXiv.
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Ian Porada, Xiyuan Zou, Jackie Chi Kit Cheung (2024). A Controlled Reevaluation of Coreference Resolution Models. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024).
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Ian Porada, Jackie Chi Kit Cheung (2024). Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution.
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Ziling Cheng, Rahul Aralikatte, Ian Porada, Cesare Spinoso-Di Piano, Jackie CK Cheung (2023). McGill BabyLM Shared Task Submission: The Effects of Data Formatting and Structural Biases. Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning.
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Ian Porada, Jackie Chi Kit Cheung (2023). McGill at CRAC 2023: Multilingual Generalization of Entity-Ranking Coreference Resolution Models. Proceedings of the CRAC 2023 Shared Task on Multilingual Coreference Resolution.
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Ian Porada, Alessandro Sordoni, Jackie Cheung (2022). Does Pre-training Induce Systematic Inference? How Masked Language Models Acquire Commonsense Knowledge. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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Ali Emami, Ian Porada, Alexandra Olteanu, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung (2021). ADEPT: An Adjective-Dependent Plausibility Task. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers).
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Ian Porada, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung (2021). Modeling Event Plausibility with Consistent Conceptual Abstraction. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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Mingde Zhao, Sitao Luan, Ian Porada, Xiao-Wen Chang, Doina Precup (2020). META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation. Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems.
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