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Collections including paper arxiv:2404.07129
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In-context Learning and Induction Heads
Paper • 2209.11895 • Published • 2 -
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Paper • 2404.07129 • Published • 3 -
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
Paper • 2403.07809 • Published • 1
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What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Paper • 2404.07129 • Published • 3 -
In-context Learning and Induction Heads
Paper • 2209.11895 • Published • 2 -
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
Paper • 2403.07809 • Published • 1
-
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Paper • 2404.07129 • Published • 3 -
In-context Learning and Induction Heads
Paper • 2209.11895 • Published • 2 -
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
Paper • 2403.07809 • Published • 1
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Explainable Lung Disease Classification from Chest X-Ray Images Utilizing Deep Learning and XAI
Paper • 2404.11428 • Published • 1 -
A Multimodal Automated Interpretability Agent
Paper • 2404.14394 • Published • 21 -
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Paper • 2404.07129 • Published • 3 -
The Geometry of Categorical and Hierarchical Concepts in Large Language Models
Paper • 2406.01506 • Published • 3
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Lumiere: A Space-Time Diffusion Model for Video Generation
Paper • 2401.12945 • Published • 86 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 24 -
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion
Paper • 2403.18818 • Published • 24 -
TC4D: Trajectory-Conditioned Text-to-4D Generation
Paper • 2403.17920 • Published • 16