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← Learning Types
Machine Learning
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Adversarial Learning
4,854 papers
Papers per year
2006: 3
2007: 1
2009: 4
2010: 6
2011: 3
2012: 5
2013: 10
2014: 6
2015: 8
2016: 18
2017: 87
2018: 261
2019: 551
2020: 588
2021: 703
2022: 633
2023: 672
2024: 579
2025: 561
2026: 155
Papers
RoCBert: Robust Chinese Bert with Multimodal Contrastive Pretraining
ACL 2022
Principled Paraphrase Generation with Parallel Corpora
ACL 2022
Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation
ACL 2022
Robust Lottery Tickets for Pre-trained Language Models
ACL 2022
Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis
ACL 2022
Pass off Fish Eyes for Pearls: Attacking Model Selection of Pre-trained Models
ACL 2022
Flooding-X: Improving BERT’s Resistance to Adversarial Attacks via Loss-Restricted Fine-Tuning
ACL 2022
SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher
ACL 2022
MPII: Multi-Level Mutual Promotion for Inference and Interpretation
ACL 2022
Adversarial Authorship Attribution for Deobfuscation
ACL 2022
“That Is a Suspicious Reaction!”: Interpreting Logits Variation to Detect NLP Adversarial Attacks
ACL 2022
Learning Disentangled Representations of Negation and Uncertainty
ACL 2022
Canary Extraction in Natural Language Understanding Models
ACL 2022
Input-specific Attention Subnetworks for Adversarial Detection
ACL 2022
Extract-Select: A Span Selection Framework for Nested Named Entity Recognition with Generative Adversarial Training
ACL 2022
Analyzing Dynamic Adversarial Training Data in the Limit
ACL 2022
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
ACL 2022
Towards Adversarially Robust Text Classifiers by Learning to Reweight Clean Examples
ACL 2022
Sibylvariant Transformations for Robust Text Classification
ACL 2022
Leveraging Expert Guided Adversarial Augmentation For Improving Generalization in Named Entity Recognition
ACL 2022
Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defense
ACL 2022
Improving Robustness of Language Models from a Geometry-aware Perspective
ACL 2022
Improving the Adversarial Robustness of NLP Models by Information Bottleneck
ACL 2022
Detection of Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimation
ACL 2022
On Length Divergence Bias in Textual Matching Models
ACL 2022
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