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Code for paper "Membership Inference Attacks Against Vision-Language Models"
LLM Council works together to answer your hardest questions
This is the repository for the USENIX Security'25 paper "Enhanced Label-Only Membership Inference Attacks with Fewer Queries" by Hao Li, Zheng Li, Siyuan Wu, Yutong Ye, Min Zhang, Dengguo Feng, and…
Fully automatic censorship removal for language models
[NeurIPS'24] HippoRAG is a novel RAG framework inspired by human long-term memory that enables LLMs to continuously integrate knowledge across external documents. RAG + Knowledge Graphs + Personali…
Source code for Imitative Membership Inference Attack
Empowering RAG with a memory-based data interface for all-purpose applications!
Official implementation of our NeurIPS 2023 paper "Augmenting Language Models with Long-Term Memory".
[AAAI'25 Oral] "MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector".
gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI
[USENIX Security 2025] SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks
Official implementation of "Data Mixture Inference: What do BPE tokenizers reveal about their training data?"
Official Implementation for the paper "d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning"
This repository contains the source code for "Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble", In Proceedings of ACM CCS 2025.
[NeurIPS D&B '25] The one-stop repository for large language model (LLM) unlearning. Supports TOFU, MUSE, WMDP, and many unlearning methods with easy feature extensibility.
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
A framework for few-shot evaluation of language models.
[ICLR2025] DiffuGPT and DiffuLLaMA: Scaling Diffusion Language Models via Adaptation from Autoregressive Models
Official PyTorch implementation for "Large Language Diffusion Models"
FlashMLA: Efficient Multi-head Latent Attention Kernels
Large Language Models Can Be Contextual Privacy Protection Learners