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Mamba-2 interpretation probes miss half of state sink

Researchers have identified a significant limitation in how Mamba-2's internal workings are understood. They found that standard probing techniques, which aim to link representational signatures to computational execution, only capture a fraction of the model's 'state sink' mechanism. A larger, 'detection layer' with similar representational patterns was missed by these single-bucket probes, highlighting a gap between representational similarity and actual functional execution in the model. AI

IMPACT Reveals limitations in current interpretability methods for state-space models, potentially impacting how future models are analyzed and understood.

RANK_REASON The cluster contains an academic paper detailing new findings about a specific AI model's architecture and interpretability. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Mamba-2 interpretation probes miss half of state sink

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The cluster contains an academic paper detailing new findings about a specific AI model's architecture and interpretability. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yuhang Jiang ·

    Detection vs. Execution: Single-Bucket Probes Miss Half the Mamba-2 State Sink

    arXiv:2606.00930v1 Announce Type: cross Abstract: Mechanistic interpretability often assumes that probes identifying a representational signature also identify the circuit executing the corresponding computation. We show that this assumption can fail systematically in Mamba-2. St…