Sorry, I just saw your question. I'm still confused by the comment system here! To answer your question, I've noticed LLMs overfit the patterns in their traini

Sorry, I just saw your question. I'm still confused by the comment system here! To answer your question, I've noticed LLMs overfit the patterns in their training data. The performance was poor when asked to "reason" in ways that diverge from what they "learned". Things less frequently mentioned in the datasets were clearly weighted as less important. And the opposite is also true. I've seen bias being amplified. For some reason, I've seen words such as "elevate" or "landscape" being overused. And obviously, I've seen so many factual errors. Search for niche topics/individuals that were not covered in the training data and you'll see incredible hallucinations.