arXiv AI By Yashal Shakti Kanungo, Sumit Negi, Aruna Rajan

Ad Headline Generation using Self-Critical Masked Language Model

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arXiv:2607. 06818v1 Announce Type: cross Abstract: For any E-commerce website it is a nontrivial problem to build enduring advertisements that attract shoppers.

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arXiv Machine Learning
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Token-Level Advertising

The paper introduces the Latent Advertiser Mixture Auction (LAMA), a token‑level advertising framework that integrates advertiser influence directly into the text generation process. Advertisers provide local continuation values that shape next‑token policies, and the platform decodes these through a latent mixture while updating an allocation posterior. LAMA is shown to satisfy Markov DSIC and IR, achieve near‑optimal KL‑regularized welfare, and, in proof‑of‑concept experiments on commercial‑search queries, improve platform welfare and revenue without compromising user‑facing response quality.

By Hanbing Liu, Bowei Zhang, Changyuan Yu, Yinyu Ye, Qi Qi
arXiv Computation and Language
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AgenticGen: Reward-Guided Agentic Video Generation for Advertising

AgenticGen is a reward‑guided framework for generating advertising videos that splits the task into strategy selection and draft generation, allowing online business feedback to supervise each stage. It learns performance‑based rewards from accumulated online metrics and rubric‑based rewards aligned with human quality standards, then applies DPO and GRPO to refine policies. Offline tests confirm the reward models, and online A/B tests on TikTok show significant gains in CTR, CVR, and advertising value over a baseline.

By Xingyuan Bu, Chengru Song, Hao Zhou, Tao Zhou, Dong Li, Wei Li, Shilong Li, Hao Shi, Yongxin Guo, Donghao Zhou, Qiangpeng Yang, Shilei Wen