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He is a researcher in artificial intelligence and an amateur researcher in mathematics. he is working on Reasoning, AI safety and Multimodal. He is also a incoming visiting faculty, National University of Singapore. He always supports Slow ScienceEmail: echo b3p0LmpAaWNsb3VkLmNvbQ== | base64 -d If you would like to join his group in any other capacity, please fill this form and then please send him a short email note without any documents. |
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Oz T. Jang [paper] (Writing) Propose combining RLHF with RLVR for improving Large Reasoning Model 2025 |
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Oz T. Jang [paper] (Writing) Propose Double Zero Self-Evolving Large Reasoning Models without data, without SFT 2025 |
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Oz T. Jang [paper] (Writing) Propose SFT-hybrid-RFT Large Reasoning Model 2025 |
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Chaoyue Zhao, Ruijie Xie, Oz T. Jang [paper] (Writing) Propose Lookahead-LSTM Bilevel Optimization for Large Reasoning Models 2025 |
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Oz T. Jang, Teng Yang, Xiaozhu Hu, Zi Yang, Chifong Wong Propose a Meta-learning optimization method named Lookahead-LSTM for improving generalization and data transferability. 2020 Spring |
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Oz T. Jang, Wei Yuan Generating multi-view videos as a world state representation,combining VLMs with text-to-video models to obtain the ability of long-horizon decision making 2023 Winter |
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Oz T. Jang, Zhigang Li, Bowen Fu Merge object 6-DoF information and improve the performance of object localization for robotic manipulation 2019 Fall |
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Starting January 2025, He has decided to commit 1~2 hours every week to provide guidance, suggestions, and/or mentorships for students from underrepresented groups or whoever is in need. Please fill in this form if you are interested. |
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