{"list":"other","total":78,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"2306.05685","title":"Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena","created":"2023-06-09","cited_by_count":8626},{"id":"1409.0575","title":"ImageNet Large Scale Visual Recognition Challenge","created":"2014-09-01","cited_by_count":8498},{"id":"1412.6572","title":"Explaining and Harnessing Adversarial Examples","created":"2014-12-20","cited_by_count":7364},{"id":"1608.06993","title":"Densely Connected Convolutional Networks","created":"2016-08-25","cited_by_count":6720},{"id":"2204.06125","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","created":"2022-04-13","cited_by_count":6585},{"id":"1706.06083","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","created":"2017-06-19","cited_by_count":6415},{"id":"2502.13923","title":"Qwen2.5-VL Technical Report","created":"2025-02-19","cited_by_count":5587},{"id":"1512.00567","title":"Rethinking the Inception Architecture for Computer Vision","created":"2015-12-02","cited_by_count":5475},{"id":"1312.6199","title":"Intriguing properties of neural networks","created":"2013-12-21","cited_by_count":5155},{"id":"2410.21276","title":"GPT-4o System Card","created":"2024-10-25","cited_by_count":4588},{"id":"1905.02244","title":"Searching for MobileNetV3","created":"2019-05-06","cited_by_count":1994},{"id":"2404.14219","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","created":"2024-04-22","cited_by_count":1917},{"id":"1607.02533","title":"Adversarial examples in the physical world","created":"2016-07-08","cited_by_count":1769},{"id":"2003.01690","title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","created":"2020-03-03","cited_by_count":1451},{"id":"1506.02025","title":"Spatial Transformer Networks","created":"2015-06-05","cited_by_count":1429},{"id":"1902.02918","title":"Certified Adversarial Robustness via Randomized Smoothing","created":"2019-02-08","cited_by_count":1340},{"id":"1511.04599","title":"DeepFool: a simple and accurate method to fool deep neural networks","created":"2015-11-14","cited_by_count":1318},{"id":"1705.07204","title":"Ensemble Adversarial Training: Attacks and Defenses","created":"2017-05-19","cited_by_count":840},{"id":"2001.03994","title":"Fast is better than free: Revisiting adversarial training","created":"2020-01-12","cited_by_count":727},{"id":"1912.00049","title":"Square Attack: a query-efficient black-box adversarial attack via random search","created":"2019-11-29","cited_by_count":685},{"id":"2010.09670","title":"RobustBench: a standardized adversarial robustness benchmark","created":"2020-10-19","cited_by_count":661},{"id":"1904.12843","title":"Adversarial Training for Free!","created":"2019-04-29","cited_by_count":643},{"id":"1803.06978","title":"Improving Transferability of Adversarial Examples with Input Diversity","created":"2018-03-19","cited_by_count":599},{"id":"1611.02770","title":"Delving into Transferable Adversarial Examples and Black-box Attacks","created":"2016-11-08","cited_by_count":536},{"id":"1711.00117","title":"Countering Adversarial Images using Input Transformations","created":"2017-10-31","cited_by_count":520},{"id":"2002.11569","title":"Overfitting in adversarially robust deep learning","created":"2020-02-26","cited_by_count":506},{"id":"2205.07460","title":"Diffusion Models for Adversarial Purification","created":"2022-05-16","cited_by_count":476},{"id":"1904.02884","title":"Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks","created":"2019-04-05","cited_by_count":442},{"id":"2103.16302","title":"Rethinking Spatial Dimensions of Vision Transformers","created":"2021-03-30","cited_by_count":361},{"id":"1908.06281","title":"Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks","created":"2019-08-17","cited_by_count":355},{"id":"1712.02976","title":"Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser","created":"2017-12-08","cited_by_count":329},{"id":"2305.16934","title":"On Evaluating Adversarial Robustness of Large Vision-Language Models","created":"2023-05-26","cited_by_count":284},{"id":"1905.07121","title":"Simple Black-box Adversarial Attacks","created":"2019-05-17","cited_by_count":251},{"id":"2103.15571","title":"Enhancing the Transferability of Adversarial Attacks through Variance Tuning","created":"2021-03-29","cited_by_count":244},{"id":"1802.05666","title":"Adversarial Risk and the Dangers of Evaluating Against Weak Attacks","created":"2018-02-15","cited_by_count":221},{"id":"2309.11751","title":"How Robust is Google's Bard to Adversarial Image Attacks?","created":"2023-09-21","cited_by_count":183},{"id":"2006.04924","title":"A Self-supervised Approach for Adversarial Robustness","created":"2020-06-08","cited_by_count":180},{"id":"2002.05990","title":"Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets","created":"2020-02-14","cited_by_count":167},{"id":"2102.00436","title":"Admix: Enhancing the Transferability of Adversarial Attacks","created":"2021-01-31","cited_by_count":156},{"id":"1907.10823","title":"Enhancing Adversarial Example Transferability with an Intermediate Level Attack","created":"2019-07-23","cited_by_count":140},{"id":"2104.12533","title":"Visformer: The Vision-friendly Transformer","created":"2021-04-26","cited_by_count":137},{"id":"2207.05382","title":"Frequency Domain Model Augmentation for Adversarial Attack","created":"2022-07-12","cited_by_count":130},{"id":"2303.03667","title":"Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks","created":"2023-03-07","cited_by_count":130},{"id":"2107.14185","title":"Feature Importance-aware Transferable Adversarial Attacks","created":"2021-07-29","cited_by_count":127},{"id":"2005.14137","title":"QEBA: Query-Efficient Boundary-Based Blackbox Attack","created":"2020-05-28","cited_by_count":104},{"id":"2204.00008","title":"Improving Adversarial Transferability via Neuron Attribution-Based Attacks","created":"2022-03-31","cited_by_count":93},{"id":"2303.09105","title":"Rethinking Model Ensemble in Transfer-based Adversarial Attacks","created":"2023-03-16","cited_by_count":89},{"id":"2111.10752","title":"Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability","created":"2021-11-21","cited_by_count":84},{"id":"2012.03528","title":"Backpropagating Linearly Improves Transferability of Adversarial Examples","created":"2020-12-07","cited_by_count":79},{"id":"2007.06765","title":"Patch-wise Attack for Fooling Deep Neural Network","created":"2020-07-14","cited_by_count":78},{"id":"2106.04169","title":"On Improving Adversarial Transferability of Vision Transformers","created":"2021-06-08","cited_by_count":70},{"id":"2210.05968","title":"Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation","created":"2022-10-12","cited_by_count":68},{"id":"2308.10299","title":"Boosting Adversarial Transferability by Block Shuffle and Rotation","created":"2023-08-20","cited_by_count":64},{"id":"2309.14700","title":"Structure Invariant Transformation for better Adversarial Transferability","created":"2023-09-26","cited_by_count":62},{"id":"2011.12807","title":"SurFree: a fast surrogate-free black-box attack","created":"2020-11-25","cited_by_count":60},{"id":"2103.10609","title":"Boosting Adversarial Transferability through Enhanced Momentum","created":"2021-03-19","cited_by_count":54},{"id":"2103.01208","title":"Mind the box: $l_1$-APGD for sparse adversarial attacks on image classifiers","created":"2021-03-01","cited_by_count":51},{"id":"2112.06569","title":"Triangle Attack: A Query-efficient Decision-based Adversarial Attack","created":"2021-12-13","cited_by_count":48},{"id":"2306.05225","title":"Boosting Adversarial Transferability by Achieving Flat Local Maxima","created":"2023-06-08","cited_by_count":48},{"id":"2303.15754","title":"Transferable Adversarial Attacks on Vision Transformers with Token Gradient Regularization","created":"2023-03-28","cited_by_count":42},{"id":"2112.06011","title":"Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting","created":"2021-12-11","cited_by_count":37},{"id":"2303.15735","title":"Improving the Transferability of Adversarial Samples by Path-Augmented Method","created":"2023-03-28","cited_by_count":36},{"id":"2304.10136","title":"Diversifying the High-level Features for better Adversarial Transferability","created":"2023-04-20","cited_by_count":34},{"id":"1801.01450","title":"Quantifying Translation-Invariance in Convolutional Neural Networks","created":"2017-12-10","cited_by_count":30},{"id":"2304.13410","title":"Improving Adversarial Transferability via Intermediate-level Perturbation Decay","created":"2023-04-26","cited_by_count":29},{"id":"2306.12685","title":"Rethinking the Backward Propagation for Adversarial Transferability","created":"2023-06-22","cited_by_count":27},{"id":"2312.04960","title":"MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness","created":"2023-12-08","cited_by_count":12},{"id":"2401.08734","title":"Bag of Tricks to Boost Adversarial Transferability","created":"2024-01-16","cited_by_count":12},{"id":"2412.18844","title":"Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path","created":"2024-12-25","cited_by_count":10},{"id":"2405.16181","title":"Boosting Adversarial Transferability with Low-Cost Optimization via Maximin Expected Flatness","created":"2024-05-25","cited_by_count":7},{"id":"2311.17087","title":"Rethinking Mixup for Improving the Adversarial Transferability","created":"2023-11-28","cited_by_count":3}],"next_cursor":null}