Tootfinder

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…

When you get the option to `Sign in with Google/Microsoft/Facebook` you're really using #OAuth. Aside from those platforms knowing what you're doing everywhere all the time, there are compelling reasons for both 3rd party services and users. (not many, but a few).
But if you DO link your #Microsoft /

Poor Software Product Management Chronicles: E-Auth, I-Auth, OAuth, Fuck Off
From the This Is Why We Can't Have Nice Things department. When you are registering or logging into an online or app service and they ...

Forbes reshuffles its leadership team and forms an AI & Strategic Platforms Group to identify future revenue streams and grow its brand across social platforms (Chris Roush/Talking Biz News)
https://talkingbiznews.com/media-news/forbes-shuffles-le…

Forbes shuffles leadership, aiming for more growth - Talking Biz News
Forbes announced changes to its leadership on Monday, looking to boost its future growth and artificial intelligence opportunities. Nina Gould was promoted to chief innovation officer, overseeing Forbes’ technology and product businesses. She will oversee Forbes’ technology, product and product design, data and business intelligence, audience growth and development, accolades and eCommerce businesses and brand […]

Examining the sentiment and emotional differences in product and service reviews: The moderating role of culture
Vinh Truong (RMIT University)
https://arxiv.org/abs/2507.21057 h…

Examining the sentiment and emotional differences in product and service reviews: The moderating role of culture
This study explores how emotions and sentiments differ in customer reviews of products and services on e-commerce platforms. Unlike earlier research that treats all reviews uniformly, this study distinguishes between reviews of products, typically fulfilling basic, functional needs, and services, which often cater to experiential and emotional desires. The findings reveal clear differences in emotional expression and sentiment between the two. Product reviews frequently focus on practicality, s…

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…

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.

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…

Sources: Meta plans its fourth AI restructuring in six months, dividing Superintelligence Labs into TBD Lab, a product team, an infrastructure team, and FAIR (Kalley Huang/The Information)
https://www.theinformation.com/articles/meta-plans-fourth…

Meta Plans Fourth Restructuring of AI Efforts in Six Months
Meta Platforms is planning the fourth restructuring of its artificial intelligence efforts in six months, according to three people familiar with the matter. Meta’s new AI organization, Meta Superintelligence Labs, is expected to be divided into four groups: a new lab that has been going by TBD ...

Auctions Meet Bandits: An Empirical Analysis
Mohammad Rashid, Omid Rafieian, Soheil Ghili
https://arxiv.org/abs/2508.21162 https://arxiv.org/pdf/2508.21162…

Auctions Meet Bandits: An Empirical Analysis
Sponsored search positions are typically allocated through real-time auctions, where the outcomes depend on advertisers' quality-adjusted bids - the product of their bids and quality scores. Although quality scoring helps promote ads with higher conversion outcomes, setting these scores for new advertisers in any given market is challenging, leading to the cold-start problem. To address this, platforms incorporate multi-armed bandit algorithms in auctions to balance exploration and exploitation…

EcomMMMU: Strategic Utilization of Visuals for Robust Multimodal E-Commerce Models
Xinyi Ling, Hanwen Du, Zhihui Zhu, Xia Ning
https://arxiv.org/abs/2508.15721 https://

EcomMMMU: Strategic Utilization of Visuals for Robust Multimodal E-Commerce Models
E-commerce platforms are rich in multimodal data, featuring a variety of images that depict product details. However, this raises an important question: do these images always enhance product understanding, or can they sometimes introduce redundancy or degrade performance? Existing datasets are limited in both scale and design, making it difficult to systematically examine this question. To this end, we introduce EcomMMMU, an e-commerce multimodal multitask understanding dataset with 406,190 sa…

Algorithmic Collusion of Pricing and Advertising on E-commerce Platforms
Hangcheng Zhao, Ron Berman
https://arxiv.org/abs/2508.08325 https://arxiv.org/pdf/…

Algorithmic Collusion of Pricing and Advertising on E-commerce Platforms
Online sellers have been adopting AI learning algorithms to automatically make product pricing and advertising decisions on e-commerce platforms. When sellers compete using such algorithms, one concern is that of tacit collusion - the algorithms learn to coordinate on higher than competitive. We empirically investigate whether these concerns are valid when sellers make pricing and advertising decisions together, i.e., two-dimensional decisions. Our empirical strategy is to analyze competition w…

VL-CLIP: Enhancing Multimodal Recommendations via Visual Grounding and LLM-Augmented CLIP Embeddings
Ramin Giahi, Kehui Yao, Sriram Kollipara, Kai Zhao, Vahid Mirjalili, Jianpeng Xu, Topojoy Biswas, Evren Korpeoglu, Kannan Achan
https://arxiv.org/abs/2507.17080

VL-CLIP: Enhancing Multimodal Recommendations via Visual Grounding and LLM-Augmented CLIP Embeddings
Multimodal learning plays a critical role in e-commerce recommendation platforms today, enabling accurate recommendations and product understanding. However, existing vision-language models, such as CLIP, face key challenges in e-commerce recommendation systems: 1) Weak object-level alignment, where global image embeddings fail to capture fine-grained product attributes, leading to suboptimal retrieval performance; 2) Ambiguous textual representations, where product descriptions often lack cont…

Human or Robot? Evidence from Last-Mile Delivery Service
Baorui Li, Xincheng Ma, Brian Rongqing Han, Daizhong Tang, Lei Fu
https://arxiv.org/abs/2509.11562 https://

Human or Robot? Evidence from Last-Mile Delivery Service
As platforms increasingly deploy robots alongside human labor in last-mile logistics, little is known about how contextual features like product attributes, environmental conditions, and psychological mechanisms shape consumer preference in real-world settings. To address this gap, this paper conducts an empirical study on consumer choice between human versus robot service, analyzing 241,517 package-level choices from Alibaba's last-mile delivery stations. We identify how product privacy sensit…