Andrew Gambardella (高波旭)

プロフィール

高波たかなみ旭あきら（英語名: アンドリュー・ガンバルデッラ）の個人サイトです。現在は東京大学松尾研究室にて松尾豊教授の下で特任研究員としてAIの研究をしています。

1992年4月	米国ドイルスタウン生まれ
2010年5月	セントラル・バックス・ウェスト・ハイ・スクール卒業
2013年12月	カリフォルニア大学バークレー校卒業
2015年4月	ソフトバンクロボティクス研究開発員
2016年7月	Reactive, Inc. (現・Cogent Labs) 研究開発員
2021年11月	オックスフォード大学博士課程終了
2022年3月	韓国科学技術院研究員
2023年8月	東京大学特任研究員

Real-World Robot Applications of Foundation Models: A Review. Kento Kawaharazuka, Tatsuya Matsushima, Andrew Gambardella, Jiaxian Guo, Chris Paxton, Andy Zeng. Advanced Robotics, 2024. [arXiv]
gOd, mOther and sOldier: A Story of Oppression, Told Through the Lens of AI. Andrew Gambardella, Meeyung Chung, Doyo Choi, Jinjoon Lee. To Appear in Leonardo, 2023. [MIT Press Direct]

Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy Arithmetic Tasks. Andrew Gambardella, Yusuke Iwasawa, Yutaka Matsuo. ACL, 2024. [ACL Proceedings] [arXiv]
Multitask Soft Option Learning. Maximilian Igl, Andrew Gambardella, Nantas Nardelli, N. Siddharth, Wendelin Böhmer, Shimon Whiteson. In Uncertainty in Artificial Intelligence, 2020. [UAI Proceedings] [arXiv]

Detecting and Quantifying Malicious Activity with Simulation-based Inference. Andrew Gambardella, Bogdan State, Naeemullah Khan, Leo Tsourides, Philip H. S. Torr, Atılım Güneş Baydin. In International Conference on Machine Learning: Workshop on Socially Responsible Machine Learning, 2021. [arXiv]
Hierarchical Semantic Sonification for the Visually Impaired. Andrew Gambardella, Jinjoon Lee. In IJCAI: Workshop on Artificial Intelligence for Social Good, 2021. [AI4SG-21]
Simulation-Based Inference for Global Health Decisions. Christian Schroeder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Rob Zinkov, Puneet Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip Torr, Atılım Güneş Baydin. In International Conference on Machine Learning Workshop: ML for Global Health, 2020. [arXiv]

Inconsistent Tokenizations Cause Language Models to be Perplexed by Japanese Grammar. Andrew Gambardella, Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo. In submission, 2024.
Crypto-LLM: Two-Stage Language Model Pre-training with Ciphered and Natural Language Data. Yohei Kobashi, Takeshi Kojima, Andrew Gambardella, Qi Cao, Yusuke Iwasawa, Yutaka Matsuo. In submission, 2024.
Which Programming Language and What Features at Pre-training Stage Affect Downstream Logical Inference Performance?. Fumiya Uchiyama, Takeshi Kojima, Andrew Gambardella, Qi Cao, Yusuke Iwasawa, Yutaka Matsuo. In submission, 2024.
Answer When Needed, Forget When Not: Language Models Pretend to Forget via In-Context Knowledge Unlearning. Shota Takashiro, Takeshi Kojima, Andrew Gambardella, Qi Cao, Yusuke Iwasawa, Yutaka Matsuo. In submission, 2024.
Inside Head: Uncertainty Quantification for LLMs based on Internal Discrepancy. Qi Cao, Andrew Gambardella, Takeshi Kojima, Yutaka Matsuo, Yusuke Iwasawa. In submission, 2024.
Efficient Data Mosaicing with Simulation-based Inference. Andrew Gambardella, Youngjun Choi, Doyo Choi, Jinjoon Lee. ArXiv Preprint, 2023. [arXiv]
Transflow Learning: Few-shot Adaptation for Normalizing Flow Models. Andrew Gambardella, Atılım Güneş Baydin, Philip H. S. Torr. ArXiv Preprint, 2019. [arXiv]

Deep Transfer Learning with Bayesian Inference. Andrew Gambardella. DPhil Thesis, 2021. [Oxford University Research Archive]

若手研究者のためにバーチャルオフィスアワー（３０分のビデ通）を開催しています。ご興味のある方はメールをお願いします。