How would you check whether a model's errors in long-fo...

By pooling all errors into a single average, you lose visibility into the model’s performance trajectory. By segmenting the generation into buckets, you can visualize the precision curve. If precision drops as the response length increases, it indicates the model is running out of reliable information and beginning to hallucinate, which suggests that interventions like length caps or early-stop heuristics might be effective.