Robust classification

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

10 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 122 papers with code (295 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Towards Deep Learning Models Resistant to Adversarial Attacks
  19 Jun 2017 59 repositories listed Syntology ran 9 of 17 samples · 8 unverified · 13 pointer-only (licence)
  Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal.
• Certified Adversarial Robustness via Randomized Smoothing
  8 Feb 2019 12 repositories listed
  We show how to turn any classifier that classifies well under Gaussian noise into a new classifier that is certifiably robust to adversarial perturbations under the ℓ₂ norm.
• SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
  14 Nov 2019 6 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Following these guidelines, we design our Fully Convolutional Siamese tracker++ (SiamFC++) by introducing both classification and target state estimation branch(G1), classification score without ambiguity(G2), tracking…
• Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
  19 Nov 2015 5 repositories listed
  Our approach is based on an objective function that trades-off mutual information between observed examples and their predicted categorical class distribution, against robustness of the classifier to an adversarial…
• MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities
  2 May 2022 4 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  By comparing the similarities and differences between input samples and memory samples in the memory pool to give effective guesses about abnormal regions; In the inference phase, MemSeg directly determines the abnormal…
• SWAD: Domain Generalization by Seeking Flat Minima
  17 Feb 2021 4 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  Domain generalization (DG) methods aim to achieve generalizability to an unseen target domain by using only training data from the source domains.
• Masksembles for Uncertainty Estimation
  15 Dec 2020 4 repositories listed
  Our central intuition is that there is a continuous spectrum of ensemble-like models of which MC-Dropout and Deep Ensembles are extreme examples.
• Denoised Smoothing: A Provable Defense for Pretrained Classifiers
  4 Mar 2020 4 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  We present a method for provably defending any pretrained image classifier against ℓₚ adversarial attacks.
• Unlabeled Data Improves Adversarial Robustness
  31 May 2019 4 repositories listed Syntology ran 1 of 8 samples · 7 unverified
  We demonstrate, theoretically and empirically, that adversarial robustness can significantly benefit from semisupervised learning.
• Implicit Generation and Generalization in Energy-Based Models
  20 Mar 2019 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
  Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train.
• Robust Classification via a Single Diffusion Model
  24 May 2023 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified · 3 pointer-only (licence)
  As RDC does not require training on particular adversarial attacks, we demonstrate that it is more generalizable to defend against multiple unseen threats.
• Label-Noise Robust Generative Adversarial Networks
  27 Nov 2018 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  To remedy this, we propose a novel family of GANs called label-noise robust GANs (rGANs), which, by incorporating a noise transition model, can learn a clean label conditional generative distribution even when training…
• Towards the first adversarially robust neural network model on MNIST
  23 May 2018 3 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  Despite much effort, deep neural networks remain highly susceptible to tiny input perturbations and even for MNIST, one of the most common toy datasets in computer vision, no neural network model exists for which…
• Robust Classification with Convolutional Prototype Learning
  9 May 2018 3 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 3 pointer-only (licence)
  To improve the robustness, we propose a novel learning framework called convolutional prototype learning (CPL).
• Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels
  4 May 2017 3 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  To highlight, RP with a CNN classifier can predict if an MNIST digit is a "one"or "not" with only 0.
• epsilon-Mesh Attack: A Surface-based Adversarial Point Cloud Attack for Facial Expression Recognition
  11 Mar 2024 2 repositories listed
  Due to the wide application area of point clouds and the recent advancements in deep neural networks, studies focusing on robust classification of the 3D point cloud data emerged.
• Robustifying Point Cloud Networks by Refocusing
  10 Aug 2023 2 repositories listed Syntology ran 15 of 22 samples · 7 unverified · 22 pointer-only (licence)
  In this study, we develop a general mechanism to increase neural network robustness based on focus analysis.
• Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off
  18 Jun 2021 2 repositories listed
  While adversarial training has become the de facto approach for training robust classifiers, it leads to a drop in accuracy.
• Analysis of classifiers robust to noisy labels
  1 Jun 2021 2 repositories listed
  We explore contemporary robust classification algorithms for overcoming class-dependant labelling noise: Forward, Importance Re-weighting and T-revision.
• Imbalanced Image Classification with Complement Cross Entropy
  4 Sep 2020 2 repositories listed
  Recently, deep learning models have achieved great success in computer vision applications, relying on large-scale class-balanced datasets.
• Implicit Generation and Modeling with Energy Based Models
  1 Dec 2019 2 repositories listed
  Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train.
• SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification
  17 Jun 2025 1 repository listed Syntology ran 0 of 3 samples · 3 unverified · 3 pointer-only (licence)
  Our study redefines the landscape of model generalization by addressing overlooked semantic biases, establishing SCISSOR as a foundational framework for mitigating shortcut learning and fostering more robust,…
• Inherently Faithful Attention Maps for Vision Transformers
  10 Jun 2025 1 repository listed
  We introduce an attention-based method that uses learned binary attention masks to ensure that only attended image regions influence the prediction.
• Acoustic Classification of Maritime Vessels using Learnable Filterbanks
  29 May 2025 1 repository listed
  Reliably monitoring and recognizing maritime vessels based on acoustic signatures is complicated by the variability of different recording scenarios.
• CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data
  29 May 2025 1 repository listed
  Conclusion: The CNN-LSTM hybrid model effectively predicted COVID-19 severity using spike protein sequences and clinical data, highlighting the utility of AI in genomic surveillance and precision public health.
• HALO: Robust Out-of-Distribution Detection via Joint Optimisation
  27 Feb 2025 1 repository listed
  This discovery has motivated work on robust OOD detection methods that are capable of maintaining performance under various attack settings.
• Adversarial Training for Defense Against Label Poisoning Attacks
  24 Feb 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  These results underscore the potential of FLORAL to enhance the resilience of machine learning models against label poisoning threats, thereby ensuring robust classification in adversarial settings.
• An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum Optimization
  13 Jan 2025 1 repository listed
  For non-convex objectives, it achieves a query complexity of O(d^{3/2}\sqrt{n}/\epsilon^2 ) without requiring the computation ofd partial derivatives at each iteration.
• HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection
  10 Jan 2025 1 repository listed
  The first component of our approach integrates vision Transformers and convolutional nets through a hierarchical feature fusion mechanism.
• PepMNet: a hybrid deep learning model for predicting peptide properties using hierarchical graph representations
  11 Dec 2024 1 repository listed
  Peptides are a powerful class of molecules that can be applied to a range of problems including biomaterials development and drug design.

Syntology lines on 15 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.