RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Awesome list of AI reverse engineering and rebuilds: what AI agents took apart and recreated, and which ones really used REA (Reverse Engineer Anything).
AVClass malware labeling tool
Tor Iptables script is an anonymizer that sets up iptables and tor to route all services and traffic including DNS through the Tor network.
- tor
- iptables
- tor-iptables-script
- tor-ip-switcher
Code repository for "TrackEverything: Long Horizon Dense Tracking via De-Duplicating 3D Scene Representations"
- 3d-point-tracking
- point-tracking
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Visualization Package for NetworkX
Graph-linked unified embedding for single-cell multi-omics data integration
Super Next generation Advanced Reactive honEypot
99+ CLI tools to build, browse, and blend your media library
a molecular descriptor calculator
:sound: spafe: Simplified Python Audio Features Extraction
Streaming WARC/ARC library for fast web archive IO
- web-archives
- web-archiving
- warc
- pywb
OWASP Honeypot, Automated Deception Framework.
Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.
Translated麦门封神榜 (Maimen Fengshenbang, "Maimen Investiture Roll") | Where do you rank in Maimen? Claim your exclusive Maimen identity
Microsoft Python Driver for SQL Server
Python version of the SGP4 satellite position library
Deep Learning Library for Single Cell Analysis
Code for PaperRobot: Incremental Draft Generation of Scientific Ideas
- pytorch
- memory-networks
- generation
- end-to-end-learning
[Reimplementation Antol et al 2015] Keras-based LSTM/CNN models for Visual Question Answering
Sequential regulatory activity predictions with deep convolutional neural networks.
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