Probe-based data attribution for alignment

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• Probe-Based Data Attributionmethod0.906
  Linear classifier approach applied to model activations to identify which training datapoints caused undesired behaviors in post-training.
• Probe-based data attribution bridges interpretability work (probes/activations) with data-centric alignment.claim0.872
  Conceptual framing: integrates mechanistic interpretability tools with alignment-focused data curation.
• Probe-based data attribution effectively reduces harmful behaviors via data interventionsclaim0.836
  Authors' central interpretive assertion that their method meaningfully mitigates unwanted behaviors.
• Probe-based method bridges interpretability (probes/activations) with data-centric alignment workclaim0.830
  Assertion from the paper's notes that the work connects two previously separate areas: interpretability tools and data-centric alignment.
• Gradient-based data attributionmethod0.799
  Baseline method against which probe-based ranking is compared; more computationally expensive.
• Data Attributionconcept0.798
  The task of attributing model behaviors to specific training datapoints.
• Attribution Similaritymethod0.760
  Correlating attribution vectors (feature activation × logit weight of next token) across model pairs to measure functional universality
• What is the appropriate metric for measuring representational alignment, given active debate on merits and deficiencies of all proposed measures?question0.759
  Open methodological question acknowledged as limitation