Explain the lost-in-the-middle phenomenon in long contexts and how you would mitigate it.

Long-context models often underuse evidence placed far from both the beginning and end. Better retrieval, reordered evidence, hierarchical summaries, position-aware training, and explicit citation checks can reduce the failure.

Use equations or tensor shapes where they clarify the claim, then name an experiment or ablation that would distinguish competing explanations.