Adaptive Activation Cancellation for Hallucination Mitigation in Large Language Models

ArXi:2603.10195v1 Announce Type: cross Large Language Models frequently generate fluent but factually incorrect text. We propose Adaptive Activation Cancellation (AAC), a real-time inference-time framework that treats hallucination-associated neural activations as structured interference within the transformer residual stream, drawing an explicit analogy to classical adaptive noise cancellation from signal processing.