Tag
Marker is an open-source tool that converts PDFs, images, and other document formats to markdown, JSON, chunks, and HTML quickly and accurately, with optional LLM enhancement.
path_boost is a Python package implementing PathBoost, a gradient boosting algorithm for interpretable graph-level prediction. It automatically discovers predictive labeled paths in graphs, supports regression and binary classification, and is compatible with scikit-learn.
The author adapts classical Islamic hadith verification methods to create a trust framework for multi-agent AI systems, releasing it as a paper and Python package (isnad).
fast-rlm is an open-source Python tool that allows LLMs to operate within an RLM harness for recursive subagent calls, with features like spend limits and live log streaming.
mlx-code is a Python package that provides a local-first LLM coding agent for Apple Silicon, bundling an MLX inference server, multi-protocol API support, git worktree isolation, and composable multi-agent primitives.
This paper presents FederatedRSF, a Python package for federated random survival forests that handles partially overlapping medical data across institutions without sharing raw data, and demonstrates comparable performance to centralized training on breast cancer data.
A 16-year-old developer created sage-explainer, a Python package that approximates prediction sensitivity to features for black-box models like random forests and XGBoost, offering more stable results than centered finite differences.
bde is a Python package that brings sampling-based Bayesian Deep Learning to practitioners via the MILE method, combining JAX's speed with scikit-learn's API for tabular supervised learning tasks.
code-review-graph is a Python tool that builds a structural map of code using Tree-sitter, tracks incremental changes, and provides precise context to AI coding assistants via MCP, significantly reducing token usage during code review tasks.