How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
This project is a comprehensive machine learning interview guide and technical study resource designed for individuals preparing for machine learning and AI engineering roles. It provides a collection of materials and practice problems covering core algorithms, theoretical fundamentals, and the implementation of neural network architectures. The resource serves as a technical reference for generative AI development, focusing on the design and optimization of large language models and diffusion systems. It includes frameworks for system design, covering the architecture of production machine l
This is the official repository for "CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors" (ACL 2023).
This repository contains code to run the inference and evaluation of NER as described in our NAACL 2024 paper: On-the-fly Definition Augmentation of LLMs for Biomedical NER
Implementation and dataset for paper "Can MLLMs Perform Text-to-Image In-Context Learning?"
The main features of uw-madison-lee-lab/cobsat are: In Context Learning.
Projects with overlapping indexed features include: alirezadir/machine-learning-interviews — This project is a comprehensive machine learning interview guide and technical study resource designed for individuals… allenai/visprog — Official code for VisProg (CVPR 2023 Best Paper!). artpli/codeie — This is the official repository for "CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors"… baaivision/emu — Emu Series: Generative Multimodal Models from BAAI. chen700564/metaner-icl — An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition. allenai/beacon — This repository contains code to run the inference and evaluation of NER as described in our NAACL 2024 paper:…