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.
Stepwise Alignment for Constrained Language Model Policy Optimization Akifumi Wachi Thien Q. Tran Rei Sato Takumi Tanabe Y ouhei Akimoto L Y Corporation University of Tsukuba
Neural Information Processing Systems
Safety and trustworthiness are indispensable requirements for real-world applications of AI systems using large language models (LLMs).
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Towards Stable Backdoor Purification through Feature Shift Tuning
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Deep Neural Networks (DNNs) are shown vulnerable to various security threats.
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Knowledge Distillation Performs Partial Variance Reduction
Neural Information Processing Systems
Knowledge distillation is a popular approach for enhancing the performance of "student" models, with lower representational capacity, by taking advantage of
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