Search Results for "novel."
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108 projects for "novel." with 1 filter applied:
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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owllook
Vertical novel search engine with unified reading and tracking tools
Owllook is an open source vertical search engine designed for discovering and reading online novels from multiple sources. Instead of redirecting users to different sites, the system parses content from many novel platforms and presents it in a unified reading interface. It focuses on providing a simple and comfortable reading experience with features such as searching for books, following updates, bookmarking chapters, and maintaining a personal bookshelf. It aggregates results from multiple search engines and applies parsing rules to extract novel metadata, chapters, and content in a consistent format. ... -
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InkOS
Autonomous novel writing CLI AI Agent
InkOS is a multi-agent creative writing system designed to automate the production of long-form narrative content such as novels through coordinated AI workflows. The system organizes multiple specialized agents that collaborate in stages, including drafting, reviewing, editing, and refining text, with optional human checkpoints to ensure quality and coherence. Its architecture reflects a pipeline approach where each agent contributes a specific function, allowing iterative improvement... -
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Kimi K2
Kimi K2 is the large language model series developed by Moonshot AI
...It was trained on an enormous corpus of over 15.5 trillion tokens to push frontier capabilities in coding, reasoning, and general agentic tasks while addressing training stability through novel optimizer and architecture design strategies. The model family includes variants like a foundational base model that researchers can fine-tune for specific use cases and an instruct-optimized variant primed for general-purpose chat and agent-style interactions, offering flexibility for both experimentation and deployment. With its high-dimensional attention mechanisms and expert routing, Kimi-K2 excels across benchmarks in live coding, math reasoning, and problem solving. -
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Kronos
A Foundation Model for the Language of Financial Markets
...It is built as a decoder-only Transformer model trained specifically on K-line data, which captures open, high, low, close, and volume information across multiple global exchanges. The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process market behavior similarly to language. This allows Kronos to perform a variety of quantitative tasks such as forecasting, pattern recognition, and anomaly detection within financial datasets. It is optimized for the noisy and complex nature of market data, distinguishing it from general-purpose time-series models. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Z-Image
Image generation model with single-stream diffusion transformer
Z-Image is an efficient, open-source image generation foundation model built to make high-quality image synthesis more accessible. With just 6 billion parameters — far fewer than many large-scale models — it uses a novel “single-stream diffusion Transformer” architecture to deliver photorealistic image generation, demonstrating that excellence does not always require extremely large model sizes. The project includes several variants: Z-Image-Turbo, a distilled version optimized for speed and low resource consumption; Z-Image-Base, the full-capacity foundation model; and Z-Image-Edit, fine-tuned for image editing tasks. ... -
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Kimi-Audio
Audio foundation model excelling in audio understanding
...Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. It uses a novel model setup that combines continuous acoustic features with discrete semantic tokens to richly capture sound and meaning across speech, music, and environmental audio. -
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GalTransl
Automated translation solution for visual novels
GalTransl is an automated translation system specifically designed for visual novels, particularly those in the “galgame” genre, leveraging large language models to streamline and enhance the translation process. It integrates support for multiple advanced LLM providers such as GPT-4, Claude, DeepSeek, and other models, enabling high-quality, context-aware translations that go beyond traditional machine translation approaches. The platform is built to handle the unique structure of visual... -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to... -
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MoBA
MoBA: Mixture of Block Attention for Long-Context LLMs
MoBA, short for Mixture of Block Attention, is an open-source research implementation of a novel attention mechanism designed to improve the efficiency of large language models processing extremely long contexts. The architecture adapts ideas from Mixture-of-Experts networks and applies them directly to the attention mechanism of transformer models. Instead of forcing each token to attend to every other token in the sequence, MoBA divides the context into blocks and dynamically routes queries to only the most relevant segments of information. ... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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RenJS
RenJS Typescript Version
RenJS V2 is a TypeScript-based visual novel engine built on Phaser, designed to help creators develop interactive storytelling experiences. It offers a script-like syntax for defining scenes, dialogues, and character interactions. -
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SimpleLLM
950 line, minimal, extensible LLM inference engine built from scratch
SimpleLLM is a minimal, extensible large language model inference engine implemented in roughly 950 lines of code, built from scratch to serve both as a learning tool and a research platform for novel inference techniques. It provides the core components of an LLM runtime—such as tokenization, batching, and asynchronous execution—without the abstraction overhead of more complex engines, making it easier for developers and researchers to understand and modify. Designed to run efficiently on high-end GPUs like NVIDIA H100 with support for models such as OpenAI/gpt-oss-120b, Simple-LLM implements continuous batching and event-driven inference loops to maximize hardware utilization and throughput. ... -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
...The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and utilities allow researchers to reproduce sequences, generate novel views, or extract task-specific supervision. Because the data are perfectly labeled and controllable, Hypersim is well suited for pretraining and for studying domain transfer to real imagery. The repository acts as both a dataset index and a set of scripts for downloading, managing, and evaluating on standardized splits. -
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Runeset
Fast UTF-8 codepoint sets for Zig
...There may be prior art, it's remarkably difficult to search for "UTF-8 character sets" and find papers on set data structures, so I can't say with high confidence that it's truly novel; in a sense, it's an obvious extension of the widespread practice of using a pair of u64 bitmasks to detect a set of ASCII values. What I can say is: it's effective. The RuneSet struct is just a slice of u64, offering a few variations on set membership tests, depending on how confident you are that the string it's testing is valid UTF-8, and what you would like the test to do in the event that it isn't. -
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Magicoder
Empowering Code Generation with OSS-Instruct
Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real open-source examples, Magicoder aims to reduce bias and improve the reliability of code generation results compared to models trained solely on synthetic instructions. ... -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. ... -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer... -
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Ruma
A set of Rust crates for interacting with the Matrix chat network
...You can use an existing server you trust or run your own, and the servers synchronize messages seamlessly. Learn more in the Introduction to Matrix. Rust is a systems programming language from Mozilla built with safety, concurrency, and performance in mind. Its novel approach to memory safety and its rich type system make it an excellent choice for writing fast, secure, and reliable programs. -
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Apache Doris
MPP-based interactive SQL data warehousing for reporting and analysis
Apache Doris is a modern MPP analytical database product. It can provide sub-second queries and efficient real-time data analysis. With it's distributed architecture, up to 10PB level datasets will be well supported and easy to operate. Apache Doris can meet various data analysis demands, including history data reports, real-time data analysis, interactive data analysis, and exploratory data analysis. Make your data analysis easier! Support standard SQL language, compatible with MySQL... -
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IQuest-Coder-V1 Model Family
New family of code large language models (LLMs)
IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic. They support native long contexts up to 128K tokens, enabling them to reason across large codebases and multi-file interactions without context fragmentation, and include “Thinking” variants optimized for complex reasoning and “Loop” variants with recurrent mechanisms to improve inference efficiency. ... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. -
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UNO
A Universal Customization Method for Single and Multi Conditioning
...Because the project is new (see activity logs for 2025), it seems to aim at bridging between single-subject customization and multi-subject generation in generative modeling — potentially useful for personalized content creation, flexible composition, or controlled generation tasks. UNO likely offers tools to fine-tune or condition generation models so that they can incorporate novel subjects, enabling users to produce custom outputs beyond standard training distribution. -
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SIN player
An in-browser offline player for the Structured Interactive Novel form
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The Unicon Project
A modern descendant of the Icon programming language.
Unicon is a very high level object-oriented network- and graphics-savvy programming language with a syntax similar to Pascal or C. Goal-direction, backtracking, patterns and novel data structures make Unicon ideal for rapidly solving complex problems. -
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ExCon Imager
Gigapixel GPU accelerated radio interferometric imager
ExCon can create images with a very wide field of view (more than billion pixels). It implements novel gridding and image weighting algorithms. It is well suited to make ultra deep radio interferometric images, minimizing aliasing artefacts and PSF variation. NVIDIA GPU acceleration is available. JAVA/SCALA support available. -
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CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. ...
