ftramer / LM_MemorizationLinks
Training data extraction on GPT-2
☆190Updated 2 years ago
Alternatives and similar repositories for LM_Memorization
Users that are interested in LM_Memorization are comparing it to the libraries listed below
Sorting:
- ☆293Updated this week
- A codebase that makes differentially private training of transformers easy.☆175Updated 2 years ago
- Repo for arXiv preprint "Gradient-based Adversarial Attacks against Text Transformers"☆107Updated 2 years ago
- Python package for measuring memorization in LLMs.☆161Updated 3 weeks ago
- ☆75Updated 3 years ago
- ☆57Updated last year
- Official Repository for Dataset Inference for LLMs☆36Updated last year
- ☆19Updated 3 years ago
- This is the starter kit for the Trojan Detection Challenge 2023 (LLM Edition), a NeurIPS 2023 competition.☆90Updated last year
- ☆26Updated 4 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
- Source code of NAACL 2025 Findings "Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models"☆12Updated 6 months ago
- Code for watermarking language models☆80Updated 11 months ago
- Code for the paper "Weight Poisoning Attacks on Pre-trained Models" (ACL 2020)☆142Updated 3 years ago
- Implementation of the paper "Exploring the Universal Vulnerability of Prompt-based Learning Paradigm" on Findings of NAACL 2022☆30Updated 3 years ago
- Differentially-private transformers using HuggingFace and Opacus☆140Updated 11 months ago
- The repository contains the code for analysing the leakage of personally identifiable (PII) information from the output of next word pred…☆100Updated 11 months ago
- [ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer☆44Updated last year
- A re-implementation of the "Extracting Training Data from Large Language Models" paper by Carlini et al., 2020☆36Updated 3 years ago
- Code for the paper "Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models" (NAACL-…☆41Updated 4 years ago
- ☆13Updated 2 years ago
- TrojanLM: Trojaning Language Models for Fun and Profit☆16Updated 4 years ago
- ☆44Updated 6 months ago
- ☆55Updated 2 years ago
- An open-source toolkit for textual backdoor attack and defense (NeurIPS 2022 D&B, Spotlight)☆185Updated 2 years ago
- Benchmarking MIAs against LLMs.☆21Updated 10 months ago
- Röttger et al. (NAACL 2024): "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"☆106Updated 5 months ago
- A survey of privacy problems in Large Language Models (LLMs). Contains summary of the corresponding paper along with relevant code☆68Updated last year
- A toolkit to assess data privacy in LLMs (under development)☆60Updated 7 months ago
- Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)☆58Updated 2 years ago