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Contributed Spotlight Talks: Part 1
David Dohan · Winnie Xu · Sugandha Sharma · Tan Zhi-Xuan

Fri Jul 22 06:45 AM -- 07:00 AM (PDT) @
in Beyond Bayes: Paths Towards Universal Reasoning Systems »

Beyond Bayes Spotlight Talks will highlight research that is participating in the afternoon poster session. Each presenter will give a brief, 5 minute talk. Attendees are welcome to ask questions to the presenters during the ICML plenary break immediately following.

9:45 AM: Talk 1 (P23): Language Model Cascades (David Dohan, Winnie Xu)

9:50 AM: Talk 2 (P08): Map Induction: Compositional Spatial Submap Learning for Efficient Exploration in Novel Environments (Sugandha Sharma)

9:55 AM: Talk 3 (P18): Abstract Interpretation for Generalized Heuristic Search in Model-Based Planning (Tan Zhi-Xuan, Vikash K. Mansinghka)

Author Information

David Dohan (Google)
Winnie Xu (University of Toronto)
Winnie Xu

Winnie recently graduated with an H.BSc from the University of Toronto where she majored in Computer Science and specialized in Artificial Intelligence. Her research interests span broadly in generative models with probabilistic interpretations and differentiable numerical algorithms. As an undergraduate, she researched latent variable models, variational inference, and Neural ODEs / SDEs with David Duvenaud. She is currently a student researcher at Google Brain collaborating with Stanford University where she is working on efficient methods for training diffusion models and doing Bayesian program induction with large language models in reasoning tasks. In the recent past, she has also collaborated with Nvidia Research, Oxford (OATML), and Cohere AI on topics in robotics, large language models, and NLP.

Sugandha Sharma (MIT)
Tan Zhi-Xuan (Massachusetts Institute of Technology)

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