Llm Optimizers Papers
Must-read Papers on Large Language Model (LLM) as Optimizers and Automatic Optimization for Prompting LLMs.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Awesome Database Learning | 8,352 | 5 months ago | 15 | |||||||
| A list of learning materials to understand databases internals | ||||||||||
| Awesome Automl Papers | 3,607 | 2 years ago | 1 | apache-2.0 | ||||||
| A curated list of automated machine learning papers, articles, tutorials, slides and projects | ||||||||||
| Awesome System For Machine Learning | 2,244 | 6 months ago | 12 | mit | ||||||
| A curated list of research in machine learning systems (MLSys). Paper notes are also provided. | ||||||||||
| Blis | 1,741 | 1 | 5 months ago | 13 | April 02, 2022 | 94 | other | C | ||
| BLAS-like Library Instantiation Software Framework | ||||||||||
| Geneticsharp | 1,159 |  | 22 | 8 | 8 months ago | 18 | January 29, 2023 | 7 | mit | C# |
| GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). | ||||||||||
| Optnet | 321 | 4 years ago | 2 | apache-2.0 | Python | |||||
| OptNet: Differentiable Optimization as a Layer in Neural Networks | ||||||||||
| Nachospigot | 244 | 2 years ago | 31 | gpl-3.0 | Java | |||||
| NachoSpigot is a fork of TacoSpigot 1.8.9 that offers several enhancements to performance as well as bug fixes. | ||||||||||
| Svgsort | 234 | 10 months ago | 1 | other | Python | |||||
| svg path sorter for more efficient (pen)plotting. | ||||||||||
| Leo | 229 | 5 years ago | 2 | apache-2.0 | Python | |||||
| Implementation of Meta-Learning with Latent Embedding Optimization | ||||||||||
| Fewshotlearning | 199 | 7 years ago | 9 | mit | Python | |||||
| Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning" | ||||||||||
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