๐ช๐ถ๐ฑ๐ฒ๐ฟ ๐ฎ๐ป๐ฑ ๐๐ฒ๐ฒ๐ฝ๐ฒ๐ฟ ๐ก๐ฒ๐๐๐ผ๐ฟ๐ธ๐ ๐ ๐ฎ๐ธ๐ฒ ๐๐ฒ๐๐๐ฒ๐ฟ ๐๐๐ฎ๐น๐๐ฎ๐๐ผ๐ฟ๐
LLMs often struggle to grade other AI models fairly.
Small networks show bias. They favor specific styles or patterns. This creates inaccurate scores for new models.
Research shows scale changes everything.
Wider networks increase capacity. They understand more nuances in text.
Deeper networks improve reasoning. They follow complex logic better.
When you combine both, you get a fairer evaluator. Larger networks reduce bias and provide reliable scores.
Use larger models to test your AI. It ensures your results reflect true performance.
Source: https://dev.to/paperium/wider-and-deeper-llm-networks-are-fairer-llm-evaluators-5a6d
Optional learning community: https://t.me/GyaanSetuAi