StateSwap: Probing Support-Elimination Hidden States in Multiple-Choice Questions

• URL: http://arxiv.org/abs/2609.01081v2
• Date: Mon, 07 Sep 2026 09:46:01 GMT
• Title: StateSwap: Probing Support-Elimination Hidden States in Multiple-Choice Questions
• Abstract summary: We investigate whether discrepancies arise from different internal representations induced by two framings.<n>We introduce a dual-framing protocol with minimally varied prompts.<n>We find that the two framings induce separable [STATE] activations concentrated in intermediate layers.
• Score: 22.173138594307662
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language models often answer the same multiple-choice question inconsistently when it is posed under support-oriented and elimination-oriented framings. We investigate whether these discrepancies arise from different internal representations induced by the two framings. We introduce a dual-framing protocol with minimally varied prompts that use either support- or elimination-oriented framing while keeping the evaluation target fixed. To probe the internal computation, we append an untrained special token, [STATE], and treat its residual-stream activation as an intervention interface. Across both models, the two framings induce separable [STATE] activations concentrated in intermediate layers. Swapping these activations between paired prompts systematically changes predictions and improves cross-framing agreement, providing intervention-based evidence that the activations are behaviorally relevant. Beyond instance-level substitution, mean-difference steering directions derived from the dual-framing contrast exhibit more bounded layer-wise responses than matched contrastive activation addition directions under the evaluated protocol.

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