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PIQLE is a Platform Implementing Q-LEarning (and other Reinforcement Learning) algorithms in JAVA. Version 2 is a major refactoring. The core data structures and algorithms are in piqle-coreVersion2. Examples are in piqle-examplesVersion2. A complete doc
This project provides some hyperheuristics, implemented as C libraries.
A hyperheuristic can be used to handle any optimization problem, as long as you implement some simple specific code to interact with it.
Some examples/applications are also provided.
The webcam computer vision (WCCV) project focuses on computer vision algorithms and systems that follow the web cam paradigm: cheap, robust and efficient. The project comprises designs, patterns, code, tutorials and examples.
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An Java artificial intelligence platform comprising common AI tools (neural networks, genetic algorithms, wavelets, etc...) and examples. The platform focuses on ease of use and ease of integration..
This library defines classes for using genetic algorithms to do optimization in any C++ program using any representation and genetic operators. The distribution includes extensive documentation and many examples.
React app for inspecting, building and debugging with the Realtime API
...It is built as a simple frontend that developers can run locally to test and understand how Realtime API interactions work. The project is intended as an educational and debugging resource rather than a production-ready application. By offering clear examples of streaming inputs and outputs, the console helps developers accelerate prototyping of real-time AI-powered applications.
Cinefile is a prototype of a category-based method of database exploration. It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories.
Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the category-based analysis.
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Reasoning-powered OCR VLM for converting complex documents to Markdown
NuMarkdown-8B-Thinking is the first reasoning OCR vision-language model (VLM) designed to convert documents into clean Markdown optimized for retrieval-augmented generation (RAG). Built on Qwen 2.5-VL-7B and fine-tuned with synthetic Doc → Reasoning → Markdown examples, it generates thinking tokens before producing the final Markdown to better handle complex layouts and tables. It uses a two-phase training process: supervised fine-tuning (SFT) followed by reinforcement learning (GRPO) with a layout-centric reward for accuracy on challenging documents. The model excels at non-standard layouts and complex table structures, outperforming non-reasoning OCR systems like GPT-4o and OCRFlux, and competing with large closed-source reasoning models like Gemini 2.5. ...