An engineer shows you an attention heat map with most o...

Attention heat maps are not reliable indicators of whether a model actually ‘read’ or ‘overrode’ information based on a specific context chunk. It is important to distinguish between where information could potentially flow and whether the output actually changes as a result. You should cite evidence, such as Jain and Wallace (2019), which demonstrates that models can maintain equivalent predictions despite adversarial attention distributions. The most reliable way to verify the model’s reliance on a chunk is to perform an ablation study: drop the chunk, re-run the inference, and compare the outputs.