Deep Learning
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
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COSMIC: Compress Satellite Images Efficiently via Diffusion Compensation
Our insight is that satellite's earth observation photos are not just images
ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram Jungwoo Oh
Despite this remarkable progress, there is a noticeable absence of datasets that combine electrocardiogram (ECG) data with question answering.
FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor
In our study, we first present a unified theoretical framework for SNN robustness constraint, which suggests that improving the encoding method and evolution of the membrane potential leak factor in spiking neurons can improve SNN robustness.
On the Overlooked Structure of Stochastic Gradients Zeke Xie
Stochastic gradients closely relate to both optimization and generalization of deep neural networks (DNNs).
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
Then we propose a platform, coined Geom3D, which enables benchmarking the effectiveness of geometric strategies.
Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
Recent successes in natural language processing have led to the proliferation of large language models (LLMs) by multiple providers. Each LLM offering has different inference accuracy, monetary cost, and latency, and their accuracy further depends on the exact wording of the question ( i .