Tootfinder

Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
Qingyi Lu, Haotian Lyu, Jiayun Zheng, Yang Wang, Li Zhang, Chengrui Zhou
https://arxiv.org/abs/2506.06336

Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
As e-commerce platforms expand their product catalogs, accurately recommending long-tail items becomes increasingly important for enhancing both user experience and platform revenue. A key challenge is the long-tail problem, where extreme data sparsity and cold-start issues limit the performance of traditional recommendation methods. To address this, we propose a novel long-tail product recommendation mechanism that integrates product text descriptions and user behavior sequences using a large-…

I am triply cautious of this article from @…:
- OpenAI et al use the supposed danger (and thus implied power) of their own product as a marketing ploy (as the article points out)
- When a product vendor funds their own research about the potential dangers of their product, it’s more likely to be good PR than good research
- Society always engages in moral panics about new things causing addiction and psychological damage (including bicycles and novels!)
With those caveats in mind, I do think this is an issue worth watching closely. And that quote in the post? Chef’s kiss.
https://mstdn.ca/@dyckron/114796898620291517

A look at DeepSeek's impact on the AI model race and market share landscape, roughly 150 days after DeepSeek R1 shook stock markets and the Western AI world (SemiAnalysis)
https://semianalysis.com/2025/07/03/deepseek-debrief-128-days-later/

DeepSeek Debrief: >128 Days Later 
SemiAnalysis is hiring an analyst in New York City for Core Research, our world class research product for the finance industry. Please apply here It’s been a bit over 150 days since the launc…

Digital Twin-based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling
Bo Fu, Mingjie Bi, Shota Umeda, Takahiro Nakano, Youichi Nonaka, Quan Zhou, Takaharu Matsui, Dawn M. Tilbury, Kira Barton
https://arxiv.org/abs/2506.07332

Digital Twin-based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling
The increasing complexity of modern manufacturing, coupled with demand fluctuation, supply chain uncertainties, and product customization, underscores the need for manufacturing systems that can flexibly update their configurations and swiftly adapt to disturbances. However, current research falls short in providing a holistic reconfigurable manufacturing framework that seamlessly monitors system disturbances, optimizes alternative line configurations based on machine capabilities, and automate…

One way to ensure I don't buy an item is to market it "as seen on Shark Tank" -- but that's probably just me. Another way to ensure I don't buy an item is to market it as having AI features (??), and apparently that's widespread.
https://futurism.com/customers-see-ai-…

Something Hilarious Happens When Potential Customers See That a Product Has AI Features
New research explores how customers react to products that are marketed as having AI — with striking results.

Follow the user meaningfully and product growth will follow: A mixed methods case study tying UX Point of View & Growth leading to measurable impact
Neha Raghuvanshi
https://arxiv.org/abs/2506.21195

Follow the user meaningfully and product growth will follow: A mixed methods case study tying UX Point of View & Growth leading to measurable impact
Have you wondered how cross-functional teams balance between maximizing value that users derive and business growth leading to win-win situations? This case study shows how User Experience Research (UXR) and Data Science teams used mixed methods research to strategically influence Product Led Growth (PLG) for a Password Manager used by million+ users, thus allowing our users, internal teams, and business to win. The audience will take away practical lessons/techniques related to leveraging mixe…

DeepShop: A Benchmark for Deep Research Shopping Agents
Yougang Lyu, Xiaoyu Zhang, Lingyong Yan, Maarten de Rijke, Zhaochun Ren, Xiuying Chen
https://arxiv.org/abs/2506.02839

DeepShop: A Benchmark for Deep Research Shopping Agents
Web agents for online shopping have shown great promise in automating user interactions across e-commerce platforms. Benchmarks for assessing such agents do not reflect the complexity of real-world shopping scenarios, as they often consist of overly simple queries with deterministic paths, such as "Find iPhone 15." Real shopping scenarios are inherently more layered, involving multi-dimensional product attributes, search filters, and user-specific sorting preferences. To address this gap, we in…

Case Study for Developing a UXR Point of View for FinOps Product Innovation
Jason Dong, Anna Wu
https://arxiv.org/abs/2506.15314 https://

Case Study for Developing a UXR Point of View for FinOps Product Innovation
In the dynamic landscape of Cloud financial management, we are sharing a case study exploring the development of a User Experience Research (UXR) Point of View (PoV) to drive FinOps product innovation. We demonstrate how qualitative and quantitative research methods working together to navigate the challenges of understanding customer needs, aligning cross-functional teams, and prioritizing limited resources. Through a multi-phased research approach, the research team identifies opportunities, …

Just read Plantin & Thomer's article, on the changes Figshare for Institutions introduces into the provision & organization of data-management labor in libraries. The authors worry that this commercial SaaS platform for institutional & data repositories, while fulfilling a number of library needs, will have detrimental effects. While it's a good piece of infrastructure-studies research, I question some of the analysis & conclusions.

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
Jonas Lau, Annie Tran
https://arxiv.org/abs/2506.15294 h…

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
This paper discusses a popular UX research activity, feature prioritization, using the User Experience Research Point of View (UXR PoV) Playbook framework. We describe an application of multinomial logistic regression, frequently marketed as MaxDiff, for prioritizing product features in consumer product development. It addresses challenges of traditional surveying techniques. We propose a solution using MaxDiff to generate a reliable preference list with a reasonable sample size. We also adapt …

This https://arxiv.org/abs/2506.04929 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
Neural Machine Translation (NMT) has improved translation by using Transformer-based models, but it still struggles with word ambiguity and context. This problem is especially important in domain-specific applications, which often have problems with unclear sentences or poor data quality. Our research explores how adding information to models can improve translations in the context of e-commerce data. To this end we create ConECT -- a new Czech-to-Polish e-commerce product translation dataset c…

This https://arxiv.org/abs/2506.05376 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Red Teaming Roadmap Towards System-Level Safety
Large Language Model (LLM) safeguards, which implement request refusals, have become a widely adopted mitigation strategy against misuse. At the intersection of adversarial machine learning and AI safety, safeguard red teaming has effectively identified critical vulnerabilities in state-of-the-art refusal-trained LLMs. However, in our view the many conference submissions on LLM red teaming do not, in aggregate, prioritize the right research problems. First, testing against clear product safety …

Liquidity provision with $\tau$-reset strategies: a dynamic historical liquidity approach
Andrey Urusov, Rostislav Berezovskiy, Anatoly Krestenko, Andrei Kornilov
https://arxiv.org/abs/2505.15338

Liquidity provision with $τ$-reset strategies: a dynamic historical liquidity approach
Since the launch of Uniswap and other AMM protocols, the DeFi industry has evolved from simple constant product functions with uniform liquidity distribution across the entire price axis to more advanced mechanisms that allow Liquidity Providers (LPs) to concentrate capital within selected price ranges. This evolution has introduced new research challenges focused on optimizing capital allocation in Decentralized Exchanges (DEXs) under dynamic market conditions. In this paper, we present a meth…