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On the Hidden Mystery of OCR in Large Multimodal Models (OCRBench)
TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering
PyTorch implementation of the SIESTA algorithm from our TMLR-2023 paper "SIESTA: Efficient Online Continual Learning with Sleep"
Bias amplification and overconfidence in computer vision.
OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
[ICLR 2023] "More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity"; [ICML 2023] "Are Large Kernels Better Teachers than Transformers for ConvNets?"
A curated list of papers and resources about the distribution shift in machine learning.
List of papers that combine self-supervision and continual learning
PyTorch implementation of Barlow Twins.
😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness
[ICML 2022]Source code for "A Closer Look at Smoothness in Domain Adversarial Training",
See the issue board for the current status of active and prospective projects!
A Python package to assess and improve fairness of machine learning models.
LAVIS - A One-stop Library for Language-Vision Intelligence
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
[MICCAI'20] Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains & A Well-organized Multi-site Dataset
code for [ECCV 2022 paper] Contributions of Shape, Texture, and Color in Visual Recognition
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced research…
PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
The decision boundary complexity (DBC) score to define and measure the complexity of decision boundary of DNNs.