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GLinSA T: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent
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Constrained decision-making problems are pervasive across various disciplines.
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Diffuser Lite: Towards Real-time Diffusion Planning Zibin Dong 1 Jianye Hao
Neural Information Processing Systems
The capability of generating high-quality long-horizon trajectories makes it a promising research direction.
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Synergistic Dual Spatial-aware Generation of Image-to-Text and Text-to-Image Y u Zhao
Neural Information Processing Systems
In the visual spatial understanding (VSU) area, spatial image-to-text (SI2T) and spatial text-to-image (ST2I) are two fundamental tasks that appear in dual form. Existing methods for standalone SI2T or ST2I perform imperfectly in spatial understanding, due to the difficulty of 3D-wise spatial feature modeling.
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Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
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Our code is available at https://github.com/sail-sg/stde
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Zipfian Whitening
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The word embedding space in neural models is skewed, and correcting this can improve task performance.
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