Tootfinder

LLP: LLM-based Product Pricing in E-commerce
Hairu Wang, Sheng You, Qiheng Zhang, Xike Xie, Shuguang Han, Yuchen Wu, Fei Huang, Jufeng Chen
https://arxiv.org/abs/2510.09347 http…

LLP: LLM-based Product Pricing in E-commerce
Unlike Business-to-Consumer e-commerce platforms (e.g., Amazon), inexperienced individual sellers on Consumer-to-Consumer platforms (e.g., eBay) often face significant challenges in setting prices for their second-hand products efficiently. Therefore, numerous studies have been proposed for automating price prediction. However, most of them are based on static regression models, which suffer from poor generalization performance and fail to capture market dynamics (e.g., the price of a used iPho…

La confiance est révocable.
Si vous avez aimé un produit ou un logiciel, et qu'il se détériore, que ses conditions changent, qu'il ajoute des fonctions d'espionnage, vous pouvez changer d'avis et cesser de lui faire confiance et de l'utiliser.
Vous devez toujours réajuster votre jugement lorsque vous recevez de nouvelles informations.
Cela s'applique aux produits, aux plateformes, aux entreprises, aux partis politiques et aux personnes.

DirecTV launches DirecTV Elect, an AI-driven political ad platform offering access to CTV ad inventory across DirecTV and US cable networks (Matthew Keys/TheDesk.net)
https://thedesk.net/2025/11/directv-elect-political-ad-ctv-launch/

DIRECTV takes on local TV with political advertising product
November 11, 2025 - DIRECTV is launching a new product called DIRECTV Elect that gives political ad buyers greater reach through connected TV platforms.

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Huike Zou, Haiyang Yang, Yindu Su, Liyu Chen, Chengbao Lian, Qingheng Zhang, Shuguang Han, Jufeng Chen
https://arxiv.org/abs/2509.23874

Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Identifying attribute values from product profiles is a key task for improving product search, recommendation, and business analytics on e-commerce platforms, which we called Product Attribute Value Identification (PAVI) . However, existing PAVI methods face critical challenges, such as cascading errors, inability to handle out-of-distribution (OOD) attribute values, and lack of generalization capability. To address these limitations, we introduce Multi-Value-Product Retrieval-Augmented Generat…

On many platforms, we are no longer the customers, but instead have become the product. Our data, even if anonymised, is sold on to actors we never intended it to reach, who can then target us with content and advertising. This includes deliberately harmful content that leads to real-world violence, spreads misinformation, wreaks havoc on our psychological wellbeing and seeks to undermine social cohesion.
Sir T.B.L.

GSID: Generative Semantic Indexing for E-Commerce Product Understanding
Haiyang Yang, Qinye Xie, Qingheng Zhang, Liyu Chen, Huike Zou, Chengbao Lian, Shuguang Han, Fei Huang, Jufeng Chen, Bo Zheng
https://arxiv.org/abs/2509.23860

GSID: Generative Semantic Indexing for E-Commerce Product Understanding
Structured representation of product information is a major bottleneck for the efficiency of e-commerce platforms, especially in second-hand ecommerce platforms. Currently, most product information are organized based on manually curated product categories and attributes, which often fail to adequately cover long-tail products and do not align well with buyer preference. To address these problems, we propose \textbf{G}enerative \textbf{S}emantic \textbf{I}n\textbf{D}exings (GSID), a data-driven…

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network
Xin Liu, Rongwu Xu, Xinyi Jia, Jason Liao, Jiao Sun, Ling Huang, Wei Xu
https://arxiv.org/abs/2510.01801

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network
The rise of large language models (LLMs) has enabled the generation of highly persuasive spam reviews that closely mimic human writing. These reviews pose significant challenges for existing detection systems and threaten the credibility of online platforms. In this work, we first create three realistic LLM-generated spam review datasets using three distinct LLMs, each guided by product metadata and genuine reference reviews. Evaluations by GPT-4.1 confirm the high persuasion and deceptive pote…