shreyansh26 / Extracting-Training-Data-from-Large-Langauge-ModelsLinks
A re-implementation of the "Extracting Training Data from Large Language Models" paper by Carlini et al., 2020
☆37Updated 3 years ago
Alternatives and similar repositories for Extracting-Training-Data-from-Large-Langauge-Models
Users that are interested in Extracting-Training-Data-from-Large-Langauge-Models are comparing it to the libraries listed below
Sorting:
- Training data extraction on GPT-2☆191Updated 2 years ago
- The code and data for "Are Large Pre-Trained Language Models Leaking Your Personal Information?" (Findings of EMNLP '22)☆24Updated 2 years ago
- ☆295Updated last month
- Source code of NAACL 2025 Findings "Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models"☆13Updated 7 months ago
- Code for the paper "Weight Poisoning Attacks on Pre-trained Models" (ACL 2020)☆143Updated 4 years ago
- ☆39Updated 2 years ago
- ☆21Updated 4 years ago
- ☆13Updated 2 years ago
- ☆56Updated last year
- Official Repository for Dataset Inference for LLMs☆41Updated last year
- Implementation of the paper "Exploring the Universal Vulnerability of Prompt-based Learning Paradigm" on Findings of NAACL 2022☆30Updated 3 years ago
- The repository contains the code for analysing the leakage of personally identifiable (PII) information from the output of next word pred…☆100Updated last year
- ☆25Updated 4 years ago
- [ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer☆46Updated last year
- ☆43Updated 2 years ago
- Repo for arXiv preprint "Gradient-based Adversarial Attacks against Text Transformers"☆108Updated 2 years ago
- ☆75Updated 3 years ago
- Official Code for ACL 2023 paper: "Ethicist: Targeted Training Data Extraction Through Loss Smoothed Soft Prompting and Calibrated Confid…☆23Updated 2 years ago
- Code for the paper "Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models" (NAACL-…☆42Updated 4 years ago
- A codebase that makes differentially private training of transformers easy.☆176Updated 2 years ago
- Official implementation of Privacy Implications of Retrieval-Based Language Models (EMNLP 2023). https://arxiv.org/abs/2305.14888☆36Updated last year
- Differentially-private transformers using HuggingFace and Opacus☆142Updated last year
- Code for paper: "Spinning Language Models: Risks of Propaganda-as-a-Service and Countermeasures"☆22Updated 3 years ago
- A framework for adversarial attacks against token classification models☆33Updated 3 years ago
- A2T: Towards Improving Adversarial Training of NLP Models (EMNLP 2021 Findings)☆26Updated 4 years ago
- Codes and datasets of the paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment☆105Updated last year
- CodeBase for Paper: "Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers", / Interactive Demo @☆79Updated 2 years ago
- Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"☆45Updated 2 years ago
- [ACL 2023] Knowledge Unlearning for Mitigating Privacy Risks in Language Models☆82Updated last year
- Code for watermarking language models☆82Updated last year