memorization

Official Pytorch repo of CVPR'23 and NeurIPS'23 papers on understanding replication in diffusion models.

[NeurIPS 2024] Goldfish Loss: Mitigating Memorization in Generative LLMs

On Memorization of Large Language Models in Logical Reasoning

PyTorch code for FLD (Feature Likelihood Divergence), FID, KID, Precision, Recall, etc. using DINOv2, InceptionV3, CLIP, etc.

In addition to helping you memorise, this code helps you do other things that I don't remember...

A re-implementation of the "Extracting Training Data from Large Language Models" paper by Carlini et al., 2020

[TMLR 2025] On Memorization in Diffusion Models

The code and data for "Are Large Pre-Trained Language Models Leaking Your Personal Information?" (Findings of EMNLP '22)

This is the official implementation for our ACL 2024 paper: "Causal Estimation of Memorisation Profiles".

The official repository for the paper entitled "Time Travel in LLMs: Tracing Data Contamination in Large Language Models."

Official Repository for Spurious Memorization - Nature Communications 2025

[NeurIPS 2024] Source code for our paper "Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models".

Continual Memorization of Factoids in Large Language Models

Memory experiments with LLMs

Training-data memorization auditor for fine-tuned LLMs — Trainer/TRL plugin, canary MIA + regurgitation audit, Apache-2.0

[WACV, 2026] Official implementation of "A Novel Metric for Detecting Memorization in Generative Models for Brain MRI Synthesis"

Understanding the memorization property of Large Language Models using Model Attribution

Demystifying Verbatim Memorization in Large Language Models

The official repository for the paper entitled "Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models."

My Graduation Project for Faculty of Computers and Information, Helwan Univeristy, Computer Science Department