arumaekawa / dataset-distillation-with-attention-labels
Implementation of "Dataset Distillation with Attention Labels for fine-tuning BERT" (accepted by ACL2023 main (short))
☆21Updated 10 months ago
Related projects ⓘ
Alternatives and complementary repositories for dataset-distillation-with-attention-labels
- ☆38Updated 2 months ago
- Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)☆57Updated last year
- ☆64Updated 2 years ago
- Source code of FedPrompt☆10Updated 2 years ago
- ☆76Updated 2 weeks ago
- Landing Page for TOFU☆94Updated 5 months ago
- AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.☆49Updated last week
- Benchmark for federated noisy label learning☆19Updated 2 months ago
- ☆20Updated last year
- Implementaiton of "DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillation" (accepted by NAACL2024 Findings)".☆14Updated last week
- ☆34Updated 3 months ago
- [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…☆62Updated 7 months ago
- The official implement of paper "Does Federated Learning Really Need Backpropagation?"☆23Updated last year
- [ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer☆32Updated 5 months ago
- ☆28Updated 4 months ago
- [ACL 2024] Code and data for "Machine Unlearning of Pre-trained Large Language Models"☆46Updated last month
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆104Updated last year
- ☆12Updated 2 years ago
- ☆18Updated 3 years ago
- DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models (ICLR 2024)☆51Updated last month
- ☆31Updated last year
- ☆10Updated 4 years ago
- [ICLR 2023] Test-time Robust Personalization for Federated Learning☆52Updated last year
- Certified Removal from Machine Learning Models☆63Updated 3 years ago
- LLM Unlearning☆123Updated last year
- ☆31Updated 8 months ago
- Differentially-private transformers using HuggingFace and Opacus☆119Updated 2 months ago
- A codebase that makes differentially private training of transformers easy.☆158Updated last year
- ✨✨A curated list of latest advances on Foundation Models with Federated Learning☆54Updated 3 weeks ago
- ☆81Updated last year