The PyTorch open source implementation for the ACM Web Conference 2025 (WWW '25) paper "Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation".
arXiv link ACM Digital Library link
Figure 1. Illustration of the Joint Influence of Content Interests and Stylistic Preferences on Headline Personalization.
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Please cite our work if you find it useful for your research and work.
@inproceedings{lian2025panoramic,
title = {Panoramic Interests: Stylistic-Content Aware Personalized Headline Generation},
author = {Junhong Lian and Xiang Ao and Xinyu Liu and Yang Liu and Qing He},
booktitle = {Companion Proceedings of the ACM on Web Conference 2025},
year = {2025},
url = {https://doi.org/10.1145/3701716.3715539},
doi = {10.1145/3701716.3715539},
pages = {1109–1112},
numpages = {4},
series = {WWW '25}
}
Personalized news headline generation aims to provide users with attention-grabbing headlines that are tailored to their preferences. Prevailing methods focus on user-oriented content preferences, but most of them overlook the fact that diverse stylistic preferences are integral to users’ panoramic interests, leading to suboptimal personalization. In view of this, we propose a novel Stylistic-Content Aware Personalized Headline Generation (SCAPE) framework. SCAPE extracts both content and stylistic features from headlines with the aid of large language model (LLM) collaboration. It further adaptively integrates users’ long- and short-term interests through a contrastive learning-based hierarchical fusion network. By incorporating the panoramic interests into the headline generator, SCAPE reflects users’ stylistic-content preferences during the generation process. Extensive experiments on the real-world dataset PENS demonstrate the superiority of SCAPE over baselines.
Install requirements (in the cloned repository):
pip3 install -r requirements.txt
[2025-05-26] We are pleased to announce that we have released the model implementation and most of the essential code. The remaining code will be available soon.
[2025-05-21] We would like to acknowledge that the comments in this project have been automatically regenerated using Gemini-2.5-Flash.