3 repositorios
Flow-matching architectures specifically designed to generate text via continuous embeddings.
Distinct from Flow-Matching Frameworks: Specializes flow-matching for text-token generation rather than the common image-based application.
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This project is a machine learning research automation system designed to manage the full research lifecycle, from idea discovery to final paper submission. It utilizes markdown-based skill templates to execute autonomous research tasks and manage iterative loops of deep review and experimentation. The system distinguishes itself through integrated capabilities for academic communication and integrity auditing. It can automate the generation of LaTeX papers, conference slide decks, and evidence-grounded peer review rebuttals. To ensure rigor, it employs cross-model review routing and adversar
Transforms noise into clean embeddings using flow matching for continuous text generation.
AI NovelGenerator es una herramienta para generar ficción de formato largo utilizando modelos de lenguaje extensos. Funciona como un arquitecto narrativo y asistente de escritura, automatizando la creación de novelas de múltiples capítulos mientras gestiona la estructura general de la historia y el seguimiento de personajes. El proyecto se distingue por un sistema de recuperación de contexto semántico y un verificador de consistencia de historia por IA. Estas herramientas utilizan búsqueda semántica para recordar detalles específicos de la historia de capítulos anteriores y escanear el texto generado en busca de contradicciones en la trama o inconsistencias de comportamiento. El sistema cubre un ciclo de vida narrativo completo, incluyendo el diseño de la base de la historia, la construcción del mundo y la planificación de la estructura de la novela. Utiliza una canalización de múltiples etapas para redactar capítulos coherentes e incorpora un banco de trabajo de flujo de trabajo creativo para gestionar configuraciones y corrección de pruebas.
Provides automated scanning of generated text to identify logical plot contradictions and character inconsistencies.
ExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,
ExecuTorch continues text generation from a specific point in the cache, enabling stateful continuation.