REPOGEO REPORT · LITE
interpretml/DiCE
Default branch main · commit 8a3aea40 · scanned 6/24/2026, 1:21:45 PM
GitHub: 1,517 stars · 233 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface interpretml/DiCE, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Strengthen README's opening to emphasize diverse counterfactuals
Why:
CURRENTDiverse Counterfactual Explanations (DiCE) for ML How to explain a machine l
COPY-PASTE FIXDiverse Counterfactual Explanations (DiCE) for ML. DiCE stands out by generating *multiple, diverse* counterfactual explanations, offering a richer understanding of model behavior than single explanations or general XAI methods.
- mediumtopics#2Add a topic for 'diverse counterfactuals'
Why:
CURRENTcounterfactual-explanations, deep-learning, explainable-ai, explainable-ml, interpretable-machine-learning, machine-learning, xai
COPY-PASTE FIXcounterfactual-explanations, deep-learning, explainable-ai, explainable-ml, interpretable-machine-learning, machine-learning, xai, diverse-counterfactuals
- mediumcomparison#3Add a 'Comparison with other XAI tools' section
Why:
COPY-PASTE FIXAdd a new section to the README titled 'Comparison with other XAI tools' that explicitly highlights DiCE's unique focus on generating *diverse* counterfactual explanations, contrasting it with methods that provide single explanations or focus on other aspects of interpretability (e.g., SHAP, LIME).
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Alibi Explain · recommended 2×
- What-If Tool (WIT) · recommended 1×
- Counterfactual-GUIDE · recommended 1×
- FAT Forensics · recommended 1×
- SHAP · recommended 1×
- CATEGORY QUERYHow can I generate diverse counterfactual explanations to interpret my machine learning model's predictions?you: #1AI recommended (in order):
- DiCE ← you
- Alibi Explain
- What-If Tool (WIT)
- Counterfactual-GUIDE
- FAT Forensics
Show full AI answer
- CATEGORY QUERYWhat tools help explain why a deep learning model made a prediction with 'what if' scenarios?you: #3AI recommended (in order):
- SHAP
- LIME
- DiCE ← you
- Alibi Explain
- InterpretML
- Captum
- What-If Tool
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of interpretml/DiCE?passAI named interpretml/DiCE explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts interpretml/DiCE in production, what risks or prerequisites should they evaluate first?passAI named interpretml/DiCE explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo interpretml/DiCE solve, and who is the primary audience?passAI named interpretml/DiCE explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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interpretml/DiCE — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite