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How Faithful Is Trajectory-Based Data Attribution? Error Sources, Remedies, and Practical Guidelines

arXiv cs.LG · 2026-05-20

This paper provides the first systematic analysis of error sources in trajectory-based data attribution methods, identifies optimizer mismatch as the dominant error, proposes AdamW-influence to address it, and offers practical guidelines for data selection via a K-step look-ahead framework.

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