Confidence

TL;DR for operators A model saying “8/10 confident” does not mean its underlying uncertainty is approximately 20%. Across the evaluated settings, the average instance-level correlation between reported confidence and logits-based confidence is only 0.135. The more useful operating rule is narrower. First test whether reported scores vary enough to distinguish cases. Then measure whether those scores rank examples meaningfully on held-out data. Separately test whether their numerical scale agrees with the comparison signal and whether they are calibrated against correctness. Do not substitute one test for another. ...

Stop Every production LLM workflow eventually meets the same boring question: should the model answer now, think again, or throw away the current path and try something else? That question sounds less glamorous than “build a bigger model.” It is also closer to where real deployment costs live. Reasoning models can improve by sampling more answers, extending chains of thought, or running repeated critique-and-revision loops. The bill, naturally, arrives in tokens, latency, GPU capacity, and engineering patience. The last item is rarely benchmarked, perhaps because it would make too many papers look expensive. ...