gianniskalyvas/llm-posthoc-explainability

A study on post-hoc explainability in LLMs using counterfactual explanations, analyzing how model scale and prompting strategies affect explanation quality.

11
/ 100
Experimental
No License No Package No Dependents
Maintenance 10 / 25
Adoption 0 / 25
Maturity 1 / 25
Community 0 / 25

How are scores calculated?

Stars

—

Forks

—

Language

Jupyter Notebook

License

—

Category

llm-interpretability-explainability

Last pushed

Mar 04, 2026

Commits (30d)

0

GitHub
LLM Interpretability & Explainability · 51 tools

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/gianniskalyvas/llm-posthoc-explainability"

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.

51

microsoft/automated-brain-explanations

Generating and validating natural-language explanations for the brain.

48

CAS-SIAT-XinHai/CPsyCoun

[ACL 2024] CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework...

44

wesg52/universal-neurons

Universal Neurons in GPT2 Language Models

39

ICTMCG/LLM-for-misinformation-research

Paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs.

38

Explore LLM Tools

All categories Trending LLM Tool directory Insights