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Career

· Visiting Student Researcher, KAIST2024–
· PhD Student, McGill University2020–
· B.S. in Computer Science, Stevens Institute of Technology2014–2018
· Intern, Amazon
· Intern, Google Research
· Intern, Microsoft Research

Publications (23)

Modeling Event Plausibility with Consistent Conceptual Abstraction
North American Chapter of the Association for Computational Linguistics · 2021
20
cited
Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text
Conference on Empirical Methods in Natural Language Processing · 2019
13
cited
Does Pre-training Induce Systematic Inference? How Masked Language Models Acquire Commonsense Knowledge
North American Chapter of the Association for Computational Linguistics · 2021
9
cited
Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective
Annual Meeting of the Association for Computational Linguistics · 2023
8
cited
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 · 2023
8
cited
ADEPT: An Adjective-Dependent Plausibility Task
Annual Meeting of the Association for Computational Linguistics · 2021
6
cited
META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation
Adaptive Agents and Multi-Agent Systems · 2019
6
cited
A Controlled Reevaluation of Coreference Resolution Models
International Conference on Language Resources and Evaluation · 2024
4
cited
McGill at CRAC 2023: Multilingual Generalization of Entity-Ranking Coreference Resolution Models
CRAC · 2023
2
cited
Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution
Conference on Computational Natural Language Learning · 2024
1
cited
Faster and More Accurate Trace-based Policy Evaluation via Overall Target Error Meta-Optimization
2019
META-Learning State-based {\lambda} for More Sample-Efficient Policy Evaluation
2019
Separately Parameterizing Singleton Detection Improves End-to-end Neural Coreference Resolution
North American Chapter of the Association for Computational Linguistics · 2024
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Ian Porada | Researcher Profile | Sotabase | Sotabase