Andrew DaiI am a Researcher at Sakana AI. My research background spans Large Language Models (LLMs), Quality Diversity (QD), and open-endedness. I also worked as an AI Researcher at Aleph Alpha. My humble beginnings started with Mechanical Engineering in Trinity College Dublin, where I co-founded Formula Trinity Autonomous with amazing close friends and teammates. After reading Ken and Joel's book in 2021 with close friends, I've learned that ambitious objectives can deceive us from greatness, inspiring me on a collaborative journey to reflect on the way that I (and artificial systems that I build with my team) can "achieve our highest goals by being willing to abandon them", ultimately making us more creative. GitHub / Google Scholar / Twitter / LinkedIn |
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ResearchAuthors marked with an asterisk (*) denote equal contribution first authors. Representative works are highlighted. |
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Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsAlex Havrilla, Andrew Dai, Laura O'Mahony, Koen Oostermeijer, Vera Zisler, Alon Albalak, Fabrizio Milo, Sharath Chandra Raparthy, Kanishk Gandhi, Baber Abbasi, Duy Phung, Maia Iyer, Dakota Mahan, Chase Blagden, Srishti Gureja, Mohammed Hamdy, Wen-Ding Li, Giovanni Paolini, Pawan Sasanka Ammanamanchi, Elliot Meyerson arXiv pre-print, 2024 arXiv Investigates quality, diversity, and complexity (QDC) of LLM synthetic data (data evaluation/downstream model effects, and data generation methods) |
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From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language ModelsEleni Nisioti*, Claire Glanois*, Elias Najarro, Andrew Dai, Elliot Meyerson, Joachim Winther Pedersen, Laetitia Teodorescu, Conor F. Hayes, Shyam Sudhakaran, Sebastian Risi ALIFE, 2024 arXiv Investigates how LLMs can serve as tools in ALife research and how ALife principles can enhance LLM development. |
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Quality-Diversity through AI FeedbackHerbie Bradley*, Andrew Dai*, Hannah Teufel, Jenny Zhang, Koen Oostermeijer, Marco Bellagente, Jeff Clune, Kenneth Stanley, Grégory Schott, Joel Lehman ICLR, 2024 project page / arXiv / code / blog QDAIF utilizes LMs to both vary texts and evaluate subjective quality/diversity of creative texts, enabling search of diverse high-quality solutions in vast spaces of subjectivity. |
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MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image GenerationMarco Bellagente*, Manuel Brack*, Hannah Teufel*, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andres Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach NeurIPS, 2023 project page / arXiv MF image-gen system enables expression of complex, nuanced concepts with arbitrarily interleaved inputs of multiple modalities and languages. |
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Interpretable Video Transformers in Imitation Learning of Human DrivingAndrew Dai, Wenliang Qiu, Bidisha Ghosh 3rd ICML 2021 Workshop on Human in the Loop Learning, 2021 ViTs applied to behavioural cloning for AVs from offline video data, lending itself to more interpretable decision-making. |
Other ProjectsThese include coursework, side projects and unpublished research work. |
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Neural Radiance Fields (and Friends)TCD CS7GV4: Augmented Reality 2021-07-21 code / video / report Applying advancements in NeRF (e.g. NeX-MPI, PlenOctrees) to AR demos within a home (and notebook). |
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Formula Trinity AutonomousTCD Extracurricular 2020-09-01 tutorial Autonomous Racing (Formula Student Driverless racing, F1TENTH) is cool - co-founded with Jakub Pyszka, Senan Stanley, Katherine Hardgrave, and curious TCD students |
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Ground and UAV Robot Sim ControlNUS EE4308: Autonomous Mobile Robots 2020-05-11 code / report Control, state estimation, perception, path planning on sim robots. Project done while on exchange in Year 4. |
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Design and source code from Jon Barron's website. Jekyll Now fork of design from Leonid Keselman |