Mathematical Visual Instruction Tuning for Multi-modal Large Language Models

😎 up-to-date & curated list of awesome LMM hallucinations papers, methods & resources.

visual question answering prompting recipes for large vision-language models

Landing Page for TOFU

[知识编辑] Must-read Papers on Knowledge Editing for Large Language Models.

Attempt at reproducing the metric from Neurips 2023 Unlearning Challenge on Kaggle. Code for training checkpoints on retain set and unlearning several models in parallel

Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems

👋 Influenciae is a Tensorflow Toolbox for Influence Functions

A complete alternative for Overleaf with VSCode + Web + Git Integration + Copilot + Grammar & Spell Checker + Live Collaboration Support. Based on GitHub Codespace and Dev container.

Code related to the paper "Machine Unlearning of Features and Labels"

Elegant LaTeX Template for Working Papers

Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models

Code for "Few Clean Instances Help Denoising Distant Supervision" ( Coling 2022)

Tools for checking ACL paper submissions

[NeurIPS 2019] Deep Leakage From Gradients

Methods for removing learned data from neural nets and evaluation of those methods

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Existing Literature about Machine Unlearning

MLNLP社区用来更好进行论文搜索的工具。Fully-automated scripts for collecting AI-related papers

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

华东师范大学 校园网网关一键登录

Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)

[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs

MLNLP社区用来帮助缩短参考文献的工具。A tool for simplifying bibtex with official info

The official implementation of "Distilling Relation Embeddings from Pre-trained Language Models, EMNLP 2021 main conference", a high-quality relation embedding based on language models.

Model interpretability and understanding for PyTorch

This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.