Wang-ML-Lab/interpretable-foundation-models
[ICML 2024] Probabilistic Conceptual Explainers (PACE): Trustworthy Conceptual Explanations for Vision Foundation Models
No commits in the last 6 months.
Stars
18
Forks
4
Language
Python
License
—
Category
Last pushed
Sep 25, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/Wang-ML-Lab/interpretable-foundation-models"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
filipnaudot/llmSHAP
llmSHAP: a multi-threaded explainability framework using Shapley values for LLM-based outputs.
microsoft/automated-brain-explanations
Generating and validating natural-language explanations for the brain.
CAS-SIAT-XinHai/CPsyCoun
[ACL 2024] CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework...
wesg52/universal-neurons
Universal Neurons in GPT2 Language Models
ICTMCG/LLM-for-misinformation-research
Paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs.