Trustworthy-ML-Lab
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Label-free-CBM
Label-free-CBM Public[ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled concept data
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CLIP-dissect
CLIP-dissect Public[ICLR 23 spotlight] An automatic and efficient tool to describe functionalities of individual neurons in DNNs
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Linear-Explanations
Linear-Explanations Public[ICML 24] A novel automated neuron explanation framework that can accurately describe poly-semantic concepts in deep neural networks
Jupyter Notebook 11
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Describe-and-Dissect
Describe-and-Dissect Public[TMLR 25] An automated method for explaining complex neuron behaviors in deep vision models using large language models
Repositories
- posthoc-generative-cbm Public
[CVPR 2025] Concept Bottleneck Autoencoder (CB-AE) -- efficiently transform any pretrained (black-box) image generative model into an interpretable generative concept bottleneck model (CBM) with minimal concept supervision, while preserving image quality
Trustworthy-ML-Lab/posthoc-generative-cbm’s past year of commit activity - effective_skill_unlearning Public
[NAACL 25] Two novel, light-weight, and training-free skill unlearning methods for LLMs
Trustworthy-ML-Lab/effective_skill_unlearning’s past year of commit activity - Describe-and-Dissect Public
[TMLR 25] An automated method for explaining complex neuron behaviors in deep vision models using large language models
Trustworthy-ML-Lab/Describe-and-Dissect’s past year of commit activity - Concept-Bottleneck-LLM Public
Trustworthy-ML-Lab/Concept-Bottleneck-LLM’s past year of commit activity - Linear-Explanations Public
[ICML 24] A novel automated neuron explanation framework that can accurately describe poly-semantic concepts in deep neural networks
Trustworthy-ML-Lab/Linear-Explanations’s past year of commit activity
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