AI/ML●Mid
My "home rig" for iterative attribute-weighted LLM benchmarking
Home rig for attribute-weighted benchmarking lacks the polish of established eval frameworks.
Ship It
yuvalhaim
211mo ago
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LLMs' Favorite Colors
by gimlids·Apr 6, 2026·2 points·0 comments
AI Analysis
●●SolidRabbit HoleNiche Gem
Sampling hex codes from 10 LLMs exposes bias patterns useful for fingerprinting.
Strengths
- •Concrete data: 200 samples per model across 10 different open-weight LLMs.
- •Visual fingerprinting hypothesis offers a novel way to detect model distillation.
- •The simple treemap visualization makes frequency distribution across models immediately readable.
Weaknesses
- •Fingerprinting claim remains speculative without further validation or established false-positive rates.
- •Limited utility beyond curiosity; no API or tool to replicate analysis.
Category
Target Audience
AI researchers, LLM enthusiasts, curious developers
Post Description
I sampled CSS hex colors out of 10 open weight LLMs to build each model's favorite colors palette, or its flag... Interesting results?
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