aichannel

> What is RewardBench?
RewardBench tests how well AI models can judge which response is better when given two options. Think of it like a taste test - the AI sees two answers to a question and must pick the superior one. It measures accuracy across different scenarios like following instructions, avoiding harmful content, and logical reasoning.

> What is an emergent rubric?
Traditional models use fixed rules i.e. "longer is better". An emergent rubric means the model creates custom evaluation criteria for each specific situation. It's like a teacher who adapts grading criteria for each unique assignment rather than using the same checklist for everything.

> Key insights
- Generate custom rubrics on-the-fly for each specific task (not using fixed rules)

- Provide reasoning for their scores, not just numbers

- j1-micro (1.7B parameters): Achieves 80.7% on RewardBench - matching GPT-4o-mini / Claude 3 Opus

- j1-nano (0.6B): At 62.4%, smaller than many phone apps

> What is RewardBench?
RewardBench tests how well AI models can judge which response is better when given two options. Think of it like a taste test - the AI sees two answers to a question and must pick the superior one. It measures accuracy across different scenarios like following instructions, avoiding harmful content, and logical reasoning.

> What is an emergent rubric?
Traditional models use fixed rules i.e. "longer is better". An emergent rubric means the model creates custom evaluation criteria for each specific situation. It's like a teacher who adapts grading criteria for each unique assignment rather than using the same checklist for everything.

> Key insights
- Generate custom rubrics on-the-fly for each specific task (not using fixed rules)

- Provide reasoning for their scores, not just numbers

- j1-micro (1.7B parameters): Achieves 80.7% on RewardBench - matching GPT-4o-mini / Claude 3 Opus

- j1-nano (0.6B): At 62.4%, smaller than many phone apps

https://github.com/haizelabs/j1-micro

i dabble with ai using open identity data from crypto https://alexpaden.tech

You’ve to train the model and then the model is the replacement, unless I’m misunderstanding your question the GitHub readme is a tutorial

You’ve to train the model and then the model is the replacement, unless I’m misunderstanding your question the GitHub readme is a tutorial

https://github.com/haizelabs/j1-micro

I gave this a read and I’ll like to ask how the use of emergent rubrics in RewardBench improve the evaluation of AI models compared to traditional fixed-rule approaches?