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My research interest lies in deep reinforcement learning (RL), particularly in devising intelligent agents capable of solving novel tasks. I believe such a goal can be achieved by learning proper abstractions, utilizing language models, and taking model-based approaches.
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Under Review CODE / arXiv We propose COCOA, a novel approach for addressing distributional shifts in offline RL (batch RL). COCOA encourages conservatism within the compositional input space of both the policy and Q-function, independently of the commonly employed behavioral conservatism. |
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Jaewoo Ahn, ACL, 2023 CODE / arXiv We construct a multimodal persona-grounded dialogue dataset, MPChat, accompanied with entailment labels. The multimodal persona consists of image-text pairs that represent one's episodic memories. We show the role of visual modality is crucial in MPChat through three benchmark tasks. |
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Master's Student in Artificial Intelligence |
Mar. 2022 - Present |
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B.S. in Statistics B.S. in Artificial Intelligence |
Mar. 2017 - Feb. 2022 |
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Exchange Student |
Fall 2019 |
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Mar. 2014 - Feb. 2017 |
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Machine Learning Researcher |
Jun. 2021 - Aug. 2021 |
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Research Intern |
Mar. 2021 - Jun. 2021 |
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Research Intern |
Jan. 2020 - Jun. 2020 |
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Mar. 2017 - Feb. 2021 |
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Spring 2017 |
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Mar. 2015 - Feb. 2017 |
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