Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment
Neural Information Processing Systems
Preferences serve as an alternative but recent work rarely considers preference learning given multiple tasks.
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Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
Neural Information Processing Systems
A VSR, respectively) has traditionally been conducted independently.
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The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information Diyuan Wu
Neural Information Processing Systems
We show for the first time that this leads both to improved convergence bounds under standard assumptions.
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Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models
Neural Information Processing Systems
Imagine observing someone scratching their arm; to understand why, additional context would be necessary. However, spotting a mosquito nearby would immediately offer a likely explanation for the person's discomfort, thereby alleviating
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