cmhcbb / Seq2Sick

Related projects: ⓘ

• lushleaf / Structure-free-certified-NLP
  SAFER: A Structure-free Approach For cErtified Robustness to Adversarial Word Substitutions (ACL 2020)
  ☆27Updated 3 years ago
• JHL-HUST / PWWS
  Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency
  ☆66Updated last year
• robinjia / certified-word-sub
  Official repository for Jia, Raghunathan, Göksel, and Liang, "Certified Robustness to Adversarial Word Substitutions" (EMNLP 2019)
  ☆39Updated 4 years ago
• cecilialeiqi / adversarial_text
  to add
  ☆20Updated 4 years ago
• AI-secure / T3
  [EMNLP 2020] "T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack" by Boxin Wang, Hengzhi Pei, Boyuan Pan, Q…
  ☆26Updated 2 years ago
• AnyiRao / WordAdver
  Code for ACL2018 HotFlip: White-Box Adversarial Examples for Text Classification, Word-level Adversarial Examples
  ☆32Updated 5 years ago
• dugu9sword / dne
  ACL 2021 - Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble
  ☆15Updated last year
• neulab / RIPPLe
  Code for the paper "Weight Poisoning Attacks on Pre-trained Models" (ACL 2020)
  ☆137Updated 2 years ago
• joey1993 / bert-defender
  codes for paper "learning to discriminate perturbations for blocking adversarial attacks in text classification" in EMNLP19
  ☆15Updated 4 years ago
• JHL-HUST / FGPM
  Adversarial Training with Fast Gradient Projection Method against Synonym Substitution based Text Attacks
  ☆23Updated 3 years ago
• nesl / nlp_adversarial_examples
  Implementation code for the paper "Generating Natural Language Adversarial Examples"
  ☆167Updated 5 years ago
• RockyLzy / TextDefender
  codes for "Searching for an Effective Defender:Benchmarking Defense against Adversarial Word Substitution"
  ☆30Updated 10 months ago
• zhengliz / natural-adversary
  Generating Natural Adversarial Examples, ICLR 2018
  ☆142Updated 6 years ago
• cookielee77 / CLARE
  Contextualized Perturbation for Textual Adversarial Attack, NAACL 2021
  ☆41Updated 3 years ago
• aonotas / interpretable-adv
  Code for Interpretable Adversarial Perturbation in Input Embedding Space for Text, IJCAI 2018.
  ☆41Updated 4 years ago
• danishpruthi / Adversarial-Misspellings
  ☆62Updated 2 years ago
• alvinchangw / CARA_EMNLP2020
  Implementation for Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder (EMNLP-Findings 2020)
  ☆15Updated 3 years ago
• Hsuan-Tung / universal_attack_natural_trigger
  Natural Universal Trigger Search (NUTS)
  ☆21Updated 3 years ago
• vikramnitin9 / adversarial-learning-literature
  ☆37Updated 4 years ago
• AI-secure / InfoBERT
  [ICLR 2021] "InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective" by Boxin Wang, Shuohang Wang, Y…
  ☆82Updated 10 months ago
• camelop / NLP-Robustness
  OOD Generalization and Detection (ACL 2020)
  ☆60Updated 4 years ago
• csong27 / collision-bert
  ☆28Updated 3 years ago
• shizhouxing / Robustness-Verification-for-Transformers
  [ICLR 2020] Code for paper "Robustness Verification for Transformers"
  ☆25Updated last year
• Eric-Wallace / adversarial-mt
  Code for "Imitation Attacks and Defenses for Black-box Machine Translations Systems"
  ☆36Updated 4 years ago
• zjiehang / RanMASK
  For Certified Robustness to Text Adversarial Attacks by Randomized [MASK]
  ☆15Updated 2 years ago
• lancopku / RAP
  Code for the paper "RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models" (EMNLP 2021)
  ☆20Updated 2 years ago
• RishabhMaheshwary / hard-label-attack
  Natural Language Attacks in a Hard Label Black Box Setting.
  ☆40Updated 3 years ago
• lancopku / Embedding-Poisoning
  Code for the paper "Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models" (NAACL-…
  ☆34Updated 3 years ago
• thunlp / NeuBA
  ☆22Updated 3 years ago
• QData / TextAttack-A2T
  A2T: Towards Improving Adversarial Training of NLP Models (EMNLP 2021 Findings)
  ☆23Updated 3 years ago