Multimodal Language Models Benchmarked Against the NRC Reactor Operator Licensing Examination: Fine-Tuning and Retrieval Strategies
The episode analyzes benchmarking multimodal language models against the rigorous NRC Reactor Operator Licensing Examination using Gemma four 31B-IT. Researchers tested various fine-tuning methods, finding that while Supervised Fine-Tuning performed strongly, the model's pooled accuracy fell just under human passing standards. This suggests that current AI systems are best used as powerful assistive tools rather than regulatory replacements.