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LLM-as-a-Verifier is a general-purpose framework that provides fine-grained feedback for any agent without requiring additional training. It achieves SOTA performance across coding, robotics, and medical agentic benchmarks.

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

  • singan
  • gan
  • official
  • single-image

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

  • segmentation
  • semantic-segmentation
  • cityscapes
  • pascal-context

KiCAD MCP is a Model Context Protocol (MCP) implementation that enables Large Language Models (LLMs) like Claude to directly interact with KiCAD for printed circuit board design.

Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.

100+ installable Claude skills covering Engineering areas such as, ISO 26262 functional safety, ISO/SAE 21434 cybersecurity, ISO 21448 SOTIF, AIAG-VDA quality (APQP/PPAP/FMEA), Automotive SPICE, and continuous improvement tools — every builder paired with a confirmation reviewer.

  • apqp
  • aspice
  • automotive
  • autosar