Eric Mitchell

TL;DR: FlyWire, an online community for proofreading neural circuits in a fly brain, is presented and it is demonstrated how FlyWire enables circuit analysis by reconstructing and analysing the connectome of mechanosensory neurons.

TL;DR: In this paper, the authors present a unique functional connectomics dataset that contains calcium imaging of an estimated 75,000 neurons from primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm), that were recorded while a mouse viewed natural movies and parametric stimuli.

TL;DR: The authors provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e. g.g. model architectures, training procedures, data, systems, security, evaluation, theory) to their applications.

TL;DR: In this article , Mitchell et al. demonstrate that text sampled from an LLM tends to occupy negative curvature regions of the model's log probability function and define a new curvature-based criterion for judging if a passage is generated from a given LLM.

TL;DR: This paper introduces the offline meta-reinforcement learning (offline meta-RL) problem setting and proposes an algorithm that performs well in this setting, and proposes MACAW, an optimization-based meta-learning algorithm that uses simple, supervised regression objectives for both the inner and outer loop of meta-training.