Ghost Context Measuring Cross-Context Interference in Long-Context Language Models
This work evaluates three widely used models across a 272-case corpus using a mask-and-rerun causal attribution protocol with dual-judge calibration and finds that Ghost Context is not only detectable but correctable.
Rohith Namboothiri
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