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LCM-Promo: An LLM-Based Uplift Model for Promotion Allocation

Paper recorded by Signals 4 on 2026-10-27 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-27 on arXiv · recorded by Signals 4 on 2026-10-28

Category: cs.LG · 机器学习 · first seen 2026-10-28

Abstract

We present LCM-Promo, an LLM-based uplift model for promotion allocation. LCM-Promo is a task-specific Large Commerce Model (LCM): a finetuned LLM trained on transactional commerce data to predict user intent and promotion response. It learns monotonic promotion-response curves from production logs by interpreting single-token outputs as conversion-threshold probabilities, while conditioning on se

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#156 most recent of 749 cs.LG papers we have recorded · ↑ newer: Spectral Braids: A Topological Descriptor for Dynamic Directed Network · ↓ older: Pneuma: A Large-Scale Real-World Time Series Benchmark for Commercial
Cite this page: LCM-Promo: An LLM-Based Uplift Model for Promotion Allocation: the #156 most recent of 749 cs.LG papers we have recorded (as of 2026-10-27). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/lcm-promo-an-llm-based-uplift-model-for-promotion-allocation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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