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Causal Inference with the Napkin Graph

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arXiv:2512. 19861v2 Announce Type: replace-cross Abstract: Unmeasured confounding can render identification strategies based on adjustment functionals invalid.

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Authors: Anna Guo, Lin Liu, David Benkeser, Razieh Nabi
Released: 2026-06-26 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Causal Inference with the Napkin Graph overlaps with clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "A pretraining-data-poisoned Qwen3-4B backdoor only fires on the exact trigger tokens — paraphrases don't activate it, and base-model similarity to the trigger doesn't predict which inputs fire (MODERATE confidence)". Matching terms: class, under, line, rate, implement, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2512.19861

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