collaborators

9 papers

cs.CL2026

R^3: Advertisement Compliance Rectification via Group-Relative Experience Extractor and Curriculum Reinforcement

Yuan Chen, Zhenyu Hu, Mengge Xue +5

Rigorous content moderation is crucial for online advertising but leads to millions of daily rejections. This scale renders manual rectification infeasible, particularly for video…

cs.CL2026

Decoding Multimodal Cues: Unveiling the Implicit Meaning Behind Hateful Videos

Junyu Lu, Deyi Ji, Liqun Liu +9

Hateful videos have become prevalent on online platforms, highlighting an urgent need for effective detection. However, existing studies primarily focus on binary classification an…

cs.CL2026

ARGUS: Policy-Adaptive Ad Governance via Evolving Reinforcement with Adversarial Umpiring

Deyi Ji, Junyu Lu, Xuanyi Liu +7

Online advertising governance faces significant challenges due to the non-stationary nature of regulatory policies, where emerging mandates (e.g., restrictions on education or aest…

cs.CV2026

Disentangling to Re-couple: Resolving the Similarity-Controllability Paradox in Subject-Driven Text-to-Image Generation

Shuang Li, Chao Deng, Hang Chen +8

Subject-Driven Text-to-Image (T2I) Generation aims to preserve a subject's identity while editing its context based on a text prompt. A core challenge in this task is the "similari…

cs.IR2026

OneRanker: Unified Generation and Ranking with One Model in Industrial Advertising Recommendation

Dekai Sun, Yiming Liu, Jiafan Zhou +6

The end-to-end generative paradigm is revolutionizing advertising recommendation systems, driving a shift from traditional cascaded architectures towards unified modeling. However,…

cs.CL2026

Towards Faithful Industrial RAG: A Reinforced Co-adaptation Framework for Advertising QA

Wenwei Li, Ming Xu, Tianle Xia +7

Industrial advertising question answering (QA) is a high-stakes task in which hallucinated content, particularly fabricated URLs, can lead to financial loss, compliance violations,…