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ESMM: joint click and post-click conversion modeling over impressions

Contribution grade

Conversion-rate recommendation · Human-designed research method or resource

Reference score130,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Trained click and joint click–conversion objectives over all impressions using a multiplicative probability decomposition and shared embeddings, avoiding direct unstable division of separately learned small probabilities.

Scientific scope

Trained click and joint click–conversion objectives over all impressions using a multiplicative probability decomposition and shared embeddings, avoiding direct unstable division of separately learned small probabilities. The sequential click-before-conversion labeling assumption and positive click support matter. Full-impression training does not by itself certify unbiased counterfactual conversion estimates or eliminate all finite-sample selection effects; delayed feedback is explicitly outside the paper's focus. Original v1 has placeholder DOI and a2022 copyright anomaly despite its2018 arXiv identity; these are not treated as valid publication identifiers.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. The sequential click-before-conversion labeling assumption and positive click support matter. Full-impression training does not by itself certify unbiased counterfactual conversion estimates or eliminate all finite-sample selection effects; delayed feedback is explicitly outside the paper's focus. Original v1 has placeholder DOI and a2022 copyright anomaly despite its2018 arXiv identity; these are not treated as valid publication identifiers.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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