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Is it possible to obtain zero-shot generalization of vision-based RL agents without data augmentation, task-centric representations, etc? Yes! by disentangling the latent space and, you might’ve heard about this given the latest news, associative memory i.e. Hopfield models!🧵

Incredibly saddened to hear of Felix Hill's passing. His work and talk on "Environmental drivers of systematicity and generalization in a situated agent" (arxiv.org/abs/1910.00571) directly inspired my first successful PhD project. Rest in peace, Felix.

Check out our work on LLM personalization led by Anikait and Sheryl! Personally (hehe), it's really cool to see how ideas in automated few-shot task construction I explored way back before my PhD remain applicable in the era of foundation models.

Congrats Chuning and collaborators! Really nice to see work on doing joint generative modelling over all (or at least more) of our available robot data. On a personal note, I remember pushing for this high-level approach to be articulated in the robotics section of the