Search Results for "concept"
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Showing 140 open source projects for "concept"
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether vulnerabilities are genuinely exploitable. The platform is intended for developers and security teams that need rapid security assessments without the overhead of manual penetration testing engagements. ... -
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RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
RuView is an edge AI perception system that transforms ordinary WiFi signals into real-time environmental sensing and human pose estimation. Built on the concept of WiFi DensePose, it analyzes disturbances in WiFi Channel State Information (CSI) caused by human movement to reconstruct body position, breathing patterns, heart rate, and presence. Unlike traditional vision systems, RuView operates without cameras, wearables, or cloud connectivity, making it a privacy-first sensing solution. ... -
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Wfuzz
Web application fuzzer
Wfuzz provides a framework to automate web applications security assessments and could help you to secure your web applications by finding and exploiting web application vulnerabilities. Wfuzz it is based on a simple concept: it replaces any reference to the FUZZ keyword by the value of a given payload. A payload in Wfuzz is a source of data. This simple concept allows any input to be injected in any field of an HTTP request, allowing to perform complex web security attacks in different web application components such as: parameters, authentication, forms, directories/files, headers, etc. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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AI Hedge Fund
An AI Hedge Fund Team
...The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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SAM 3
Code for running inference and finetuning with SAM 3 model
...It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short phrase or exemplars, scaling to a vastly larger set of categories than traditional closed-set models. This capability is grounded in a new data engine that automatically annotated over four million unique concepts, producing a massive open-vocabulary segmentation dataset and enabling the model to achieve 75–80% of human performance on the SA-CO benchmark, which itself spans 270K unique concepts. -
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Exploitarium
A single archive of public exploit PoCs and vulnerability research
Exploitarium is a consolidated archive of public proof-of-concept vulnerability research and exploit writeups. It gathers older standalone research repositories into one place while also adding newer entries as self-contained folders. The project includes tracked examples involving software such as 7-Zip, AnyDesk, c-ares, curl, Discourse, Docker, and other targets. Its purpose is research visibility, vulnerability study, and educational review rather than normal application deployment. ... -
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Marvin
A batteries-included library for building AI-powered software
Meet Marvin: a batteries-included library for building AI-powered software. Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages, scoring sentiment, or categorizing items in your database. ... -
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discord.py-self
A fork of the popular discord.py for user accounts
...It supports areas such as sessions, read states, relationships, connections, interactions, application management, and other account-level features. The project clearly warns that automating user accounts violates Discord’s Terms of Service and is not recommended. It is best viewed as a proof-of-concept or research-oriented fork rather than a safe replacement for official Discord bot libraries. -
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Copy Fail - CVE-2026-31431
epository that demonstrates and analyzes a Linux kernel vulnerability
Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. -
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Dream Textures
Stable Diffusion built-in to Blender
Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. -
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athenaSQL
SQL builder for AWS Athena, inspired by sparkSQL
athenaSQL is Athena SQL query builder, inspired by sparkSQL. It borrow some sparkSQL’s concept sparkSQL. It was initially designed to eliminate the need for hard-coding SQL queries as strings within Python scripts and as an alternative to any bespoke SQL query templating. However, it offers the flexibility to be used in various ways as needed. -
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caveman
Why use many token when few token do trick
...Caveman embraces a philosophy of “less is more,” encouraging developers to focus on core functionality rather than framework overhead. Its design makes it particularly useful for experimentation, small tools, or proof-of-concept applications. -
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Thoth
Thoth - Personal AI Sovereignty. A local-first AI assistant
Thoth is an AI-driven system designed to support advanced reasoning, knowledge processing, or agentic workflows, likely inspired by the concept of structured intelligence and decision-making. It focuses on organizing and synthesizing information in a way that enables deeper insights and more autonomous behavior. The project may incorporate LLMs, data pipelines, and modular components to handle complex tasks such as reasoning, planning, or knowledge retrieval. Its architecture likely emphasizes extensibility, allowing developers to customize workflows or integrate external tools. ... -
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Synapse
Matrix reference homeserver
Matrix is an ambitious new ecosystem for open federated Instant Messaging and VoIP. Everything in Matrix happens in a room. Rooms are distributed and do not exist on any single server. Rooms can be located using convenience aliases like #matrix:matrix.org or #test:localhost:8448. Synapse is currently in rapid development, but as of version 0.5 we believe it is sufficiently stable to be run as an internet-facing service for real usage! Create and manage fully distributed chat rooms with no... -
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Deep Search Agent
Implement a concise and clear Deep Search Agent from 0
...It typically combines reasoning, retrieval, and iterative refinement so the agent can break down questions, gather evidence, and synthesize structured outputs. The project is positioned primarily as a proof of concept for deep research agents rather than a production-ready system. Its architecture highlights agent loops, tool calling, and stepwise execution, which are increasingly important patterns in modern AI automation. Overall, the demo serves as a practical reference for developers exploring autonomous research agents and multi-tool LLM orchestration. -
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DeepTutor
AI-Powered Personalized Learning Assistant
DeepTutor is an AI-powered tutoring and learning assistant framework designed to automatically teach, explain, and reinforce academic or technical concepts in depth according to a learner’s specific needs. It goes beyond simple Q&A by constructing multi-stage educational narratives, breaking down complex topics into sequenced “lesson steps,” and offering prompts, examples, and exercises that build on each other in a logical curriculum. The core architecture combines LLM-based reasoning with... -
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Perceval
An open source framework for programming photonic quantum computers
...It aims to be a companion tool for developing photonic circuits – for simulating and optimizing their design, modeling both the ideal and realistic behaviors, and proposing a normalized interface to control them through the concept of backends. -
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Atomic Agents
Building AI agents, atomically
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. -
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Key-book
Proofs, cases, concept supplements, and reference explanations
The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven... -
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OmniBox
Collect, organize, use, and share, all in OmniBox
...The project focuses on creating a centralized input field where users can enter commands, queries, or shortcuts that trigger actions across different applications or services. Inspired by the omnibox concept used in modern browsers, the system combines search functionality with command execution so that users can access information and perform tasks without navigating complex menus. The mirrored distribution on SourceForge exists to provide an additional download source and preserve access to the software’s source code independent of its original repository. ... -
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MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching. ... -
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Tookie-OSINT
Username OSINT tool for discovering accounts across many websites
...By entering a target username, Tookie-OSINT scans a list of supported sites and checks whether the username exists on those platforms. This approach removes the need for manual checks and significantly speeds up OSINT investigations. It is similar in concept to tools such as Sherlock, focusing on identifying user profiles across social media and other online services. Tookie-OSINT includes both command-line and optional web interface functionality, giving users flexible ways to run scans and analyze results. Tookie-OSINT was created to help beginners and aspiring security professionals learn about OSINT techniques. -
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Bindu
Bindu: Turn any AI agent into a living microservice
...The system is designed to be framework-agnostic, meaning developers can build agents using tools like LangChain, OpenAI SDK, or custom implementations and still deploy them seamlessly. Bindu also introduces the concept of an “Internet of Agents,” where multiple specialized agents collaborate, discover each other, and exchange services autonomously. -
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
...The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. The core concept of the framework is the use of semantic operators, which extend traditional relational database operations to support reasoning over text and other unstructured data. These operators allow tasks such as semantic filtering, ranking, clustering, and summarization to be expressed directly within data processing pipelines. The LOTUS engine automatically optimizes how language models are used during execution, which can significantly improve performance and reduce computational cost.
