TraceFL
warisgill
TraceFL is a novel mechanism for Federated Learning that achieves interpretability by tracking neuron provenance. It identifies clients responsible for global model predictions, achieving 99% accuracy across diverse datasets (e.g., medical imaging) and neural networks (e.g., GPT).
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2 data points · 2025-03-01 → 2026-04-01How do you feel about this project?
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Question copied to clipboardWhat is the warisgill/TraceFL GitHub project? Description: "TraceFL is a novel mechanism for Federated Learning that achieves interpretability by tracking neuron provenance. It identifies clients responsible for global model predictions, achieving 99% accuracy across diverse datasets (e.g., medical imaging) and neural networks (e.g., GPT).". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.
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