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https://openreview.net/forum?id=VLdqHdp4j1H Entropy Weighted Adversarial Training | OpenReview We propose an instance-wise entropy-weighted adversarial training to focus on more uncertain examples. adversarial training entropy weighted openreview https://openreview.net/forum?id=H1lZJpVFvr Robust Local Features for Improving the Generalization of Adversarial Training | OpenReview We propose a new stream of adversarial training approach called Robust Local Features for Adversarial Training (RLFAT) that significantly improves both the... local features adversarial training robust improving https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2022.859610/full Frontiers | Generative Adversarial Training for Supervised and Semi-supervised Learning Neural networks have played critical roles in many research fields. The recently proposed adversarial training (AT) can improve the generalization ability of... adversarial training frontiers generative supervised semi https://openreview.net/forum?id=BygzbyHFvB&ref=ruder.io FreeLB: Enhanced Adversarial Training for Natural Language Understanding | OpenReview Adversarial training, which minimizes the maximal risk for label-preserving input perturbations, has proved to be effective for improving the generalization of... training for natural language enhanced adversarial understanding openreview https://deepai.org/publication/on-the-generalization-properties-of-adversarial-training On the Generalization Properties of Adversarial Training | DeepAI Aug 15, 2020 - 08/15/20 - Modern machine learning and deep learning models are shown to be vulnerable when testing data are slightly perturbed. Theoretical ... on the adversarial training generalization properties deepai https://deepai.org/publication/interpolated-joint-space-adversarial-training-for-robust-and-generalizable-defenses Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses | DeepAI Dec 12, 2021 - 12/12/21 - Adversarial training (AT) is considered to be one of the most reliable defenses against adversarial attacks. However, models train... joint space adversarial training interpolated https://openreview.net/forum?id=BJE-4xW0W CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training | OpenReview We introduce causal implicit generative models, which can sample from conditional and interventional distributions and also propose two new conditional GANs... generative models adversarial training learning causal implicit https://openreview.net/forum?id=SJxSDxrKDr Adversarial Training and Provable Defenses: Bridging the Gap | OpenReview We propose a novel combination of adversarial training and provable defenses which produces a model with state-of-the-art accuracy and certified robustness on... bridging the gap adversarial training provable defenses openreview https://arxiv.org/html/2504.15457v4 Improving Human-AI Coordination through Online Adversarial Training and Generative Models human ai adversarial training improving coordination https://openreview.net/forum?id=vWS3gcvztz&referrer=%5Bthe%20profile%20of%20Baoyuan%20Wu%5D(%2Fprofile%3Fid%3D~Baoyuan_Wu1) Improving Fast Adversarial Training With Prior-Guided Knowledge | OpenReview Fast adversarial training (FAT) is an efficient method to improve robustness in white-box attack scenarios. However, the original FAT suffers from catastrophic... adversarial training improving fast prior guided https://openreview.net/forum?id=1EWPr0ks8I Better Diffusion Models Further Improve Adversarial Training | OpenReview It has been recognized that the data generated by the denoising diffusion probabilistic model (DDPM) improves adversarial training. After two years of rapid... diffusion models adversarial training better improve openreview https://deepai.org/publication/adversarial-training-for-multi-context-joint-entity-and-relation-extraction Adversarial training for multi-context joint entity and relation extraction | DeepAI Aug 21, 2018 - 08/21/18 - Adversarial training (AT) is a regularization method that can be used to improve the robustness of neural network methods by addin... adversarial training relation extraction multi context https://openreview.net/forum?id=BygzbyHFvB FreeLB: Enhanced Adversarial Training for Natural Language Understanding | OpenReview Adversarial training, which minimizes the maximal risk for label-preserving input perturbations, has proved to be effective for improving the generalization of... training for natural language enhanced adversarial understanding openreview https://deepai.org/publication/you-only-propagate-once-painless-adversarial-training-using-maximal-principle You Only Propagate Once: Painless Adversarial Training Using Maximal Principle | DeepAI May 2, 2019 - 05/02/19 - Deep learning achieves state-of-the-art results in many areas. However recent works have shown that deep networks can be vulnerabl... adversarial training maximal principle propagate painless https://deepai.org/publication/mutual-adversarial-training-learning-together-is-better-than-going-alone Mutual Adversarial Training: Learning together is better than going alone | DeepAI Dec 9, 2021 - 12/09/21 - Recent studies have shown that robustness to adversarial attacks can be transferred across networks. In other words, we can make a... together is better adversarial training going alone mutual learning https://deepai.org/publication/a3t-adversarially-augmented-adversarial-training A3T: Adversarially Augmented Adversarial Training | DeepAI Jan 12, 2018 - 01/12/18 - Recent research showed that deep neural networks are highly sensitive to so-called adversarial perturbations, which are tiny pertu... adversarial training augmented deepai https://deepai.org/publication/adaptive-smoothness-weighted-adversarial-training-for-multiple-perturbations-with-its-stability-analysis Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability... Oct 2, 2022 - 10/02/22 - Adversarial Training (AT) has been demonstrated as one of the most effective methods against adversarial examples. While most exis... adversarial training adaptive smoothness weighted https://arxiv.org/abs/2205.00637v1 [2205.00637v1] Enhancing Adversarial Training with Feature Separability Abstract page for arXiv paper 2205.00637v1: Enhancing Adversarial Training with Feature Separability adversarial training 2205 enhancing feature separability https://openreview.net/forum?id=U0TCTe68s41 Demystifying Adversarial Training via A Unified Probabilistic Framework | OpenReview Adversarial Training (AT) is known as an effective approach to enhance the robustness of deep neural networks. Recently researchers notice that robust models... adversarial training demystifying via unified probabilistic https://openreview.net/forum?id=jy292MSaSRd&referrer=%5Bthe%20profile%20of%20Sumukh%20K%20Aithal%5D(%2Fprofile%3Fid%3D~Sumukh_K_Aithal1) A Closer Look at Smoothness in Domain Adversarial Training | OpenReview Domain adversarial training has been ubiquitous for achieving invariant representations and is used widely for various domain adaptation tasks. In recent... a closer look in domain adversarial training smoothness openreview https://openreview.net/forum?id=BRdEBlwUW6 DAFA: Distance-Aware Fair Adversarial Training | OpenReview The disparity in accuracy between classes in standard training is amplified during adversarial training, a phenomenon termed the robust fairness problem.... adversarial training dafa distance aware fair https://arxiv.org/abs/2303.05758 [2303.05758] MIXPGD: Hybrid Adversarial Training for Speech Recognition Systems Abstract page for arXiv paper 2303.05758: MIXPGD: Hybrid Adversarial Training for Speech Recognition Systems adversarial training speech recognition 2303 hybrid systems https://deepai.org/publication/adversarial-training-with-generated-data-in-high-dimensional-regression-an-asymptotic-study Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study |... Jun 21, 2023 - 06/21/23 - In recent years, studies such as have demonstrated that incorporating additional real or generated data with pseudo-labels ... adversarial training https://openreview.net/forum?id=34yGUOcocD Adversarial Training Should Be Cast as a Non-Zero-Sum Game | OpenReview One prominent approach toward resolving the adversarial vulnerability of deep neural networks is the two-player zero-sum paradigm of adversarial training, in... non zero sum game adversarial training should be https://deepai.org/publication/combining-recurrent-neural-networks-and-adversarial-training-for-human-motion-synthesis-and-control Combining Recurrent Neural Networks and Adversarial Training for Human Motion Synthesis and Control... Jun 21, 2018 - 06/21/18 - This paper introduces a new generative deep learning network for human motion synthesis and control. Our key idea is to combine re... recurrent neural networks adversarial training https://openreview.net/forum?id=kdPcLdJbt1 Vulnerability-Aware Instance Reweighting For Adversarial Training | OpenReview Adversarial Training (AT) has been found to substantially improve the robustness of deep learning classifiers against adversarial attacks. AT involves... adversarial training vulnerability aware instance openreview https://openreview.net/forum?id=HPdxC1THU8T Revisiting adapters with adversarial training | OpenReview While adversarial training is generally used as a defense mechanism, recent works show that it can also act as a regularizer. By co-training a neural network... adversarial training revisiting adapters openreview https://www.amazon.science/blog/adversarial-training-improves-product-discovery Adversarial training improves product discovery - Amazon Science Mar 6, 2024 - Method automatically generates negative training examples for deep-learning model. adversarial training product discovery improves amazon science https://openreview.net/forum?id=6LxMeRlkWl Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs | OpenReview Large language models (LLMs) can often be made to behave in undesirable ways that they are explicitly fine-tuned not to. For example, the LLM red-teaming... adversarial training https://openreview.net/forum?id=UDJ5tOYHot&referrer=%5Bthe%20profile%20of%20Yuntian%20Chen%5D(%2Fprofile%3Fid%3D~Yuntian_Chen1) Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training | OpenReview Adversarial training is often formulated as a min-max problem however concentrating only on the worst adversarial examples causes alternating repetitive... focus on adversarial training hiders exploring hidden https://openreview.net/forum?id=w38OtHu4Ha Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study |... adversarial training https://aclanthology.org/2021.acl-long.401/ Data Augmentation with Adversarial Training for Cross-Lingual NLI - ACL Anthology Xin Dong, Yaxin Zhu, Zuohui Fu, Dongkuan Xu, Gerard de Melo. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the... data augmentation adversarial training for cross https://openreview.net/forum?id=NENo__bExYu Make Some Noise: Reliable and Efficient Single-Step Adversarial Training | OpenReview We introduce a novel single-step attack for adversarial training that can prevent catastrophic overfitting while obtaining a 3x speed-up. make some noise single step adversarial training reliable https://deepai.org/publication/ganspeech-adversarial-training-for-high-fidelity-multi-speaker-speech-synthesis GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis | DeepAI Jun 29, 2021 - 06/29/21 - Recent advances in neural multi-speaker text-to-speech (TTS) models have enabled the generation of reasonably good speech quality ... adversarial training high fidelity speech synthesis https://openreview.net/forum?id=ODkBI1d3phW Efficient and Effective Augmentation Strategy for Adversarial Training | OpenReview We propose an effective augmentation strategy for Adversarial Training that can be integrated with several Adversarial Training algorithms and data... adversarial training efficient effective augmentation strategy https://deepai.org/publication/to-be-robust-or-to-be-fair-towards-fairness-in-adversarial-training To be Robust or to be Fair: Towards Fairness in Adversarial Training | DeepAI Oct 13, 2020 - 10/13/20 - Adversarial training algorithms have been proven to be reliable to improve machine learning models' robustness against adversarial... to be adversarial training robust fair https://openreview.net/forum?id=HkgrZ0EYwB Unpaired Point Cloud Completion on Real Scans using Adversarial Training | OpenReview As 3D scanning solutions become increasingly popular, several deep learning setups have been developed for the task of scan completion, i.e., plausibly filling... point cloud adversarial training completion https://www.amazon.science/publications/smoothing-model-predictions-using-adversarial-training-procedures-for-speech-based-emotion-recognition Smoothing model predictions using adversarial training procedures for speech based emotion... Training discriminative classifiers involves learning a conditional distribution p(yi|xi), given a set of feature vectors xi and the corresponding labels yi, i... adversarial training smoothing model predictions using https://openreview.net/forum?id=I3HCE7Ro78H Finding Actual Descent Directions for Adversarial Training | OpenReview There is a subtle bug in the theory behind PGD. We show how to correct it and that it matters in practice adversarial training finding actual descent directions