Towards a Unified Multidimensional Explainability Metric: Evaluating Trustworthi
In this paper, we present a comprehensive framework for assessing the explainability of various XAI methods, such as LIME and SHAP, across multiple datasets and machine learning models, with the ultimate goal of creating a unified multidime
https://arxiv.org/abs/2607.14315v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
None
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Sector
ai
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Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
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People
G
Georgios Makridis
1.0
low confidence
G
Georgios Fatouros
1.0
low confidence
A
Athanasios Kiourtis
1.0
low confidence
D
Dimitrios Kotios
1.0
low confidence
V
Vasileios Koukos
1.0
low confidence
D
Dimosthenis Kyriazis
1.0
low confidence
J
Jonh Soldatos
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
Envariant
· Active
Interpretability and reasoning infra for foundation models.
founders not scraped yet
Marft
· Inactive
Marft creates embeddable machine learning models for application…
founders not scraped yet