Tootfinder

Gmail-App separiert Käufe und Paketverfolgung, stellt relevante Werbung heraus
Google spendiert allen Nutzern von Gmail zwei neue Funktionen. Käufe und Paketzustellungen sind im Menü zu finden, Werbung wird nach Relevanz sortiert.

TaoSR-SHE: Stepwise Hybrid Examination Reinforcement Learning Framework for E-commerce Search Relevance
Pengkun Jiao, Yiming Jin, Jianhui Yang, Chenhe Dong, Zerui Huang, Shaowei Yao, Xiaojiang Zhou, Dan Ou, Haihong Tang
https://arxiv.org/abs/2510.07972

TaoSR-SHE: Stepwise Hybrid Examination Reinforcement Learning Framework for E-commerce Search Relevance
Query-product relevance analysis is a foundational technology in e-commerce search engines and has become increasingly important in AI-driven e-commerce. The recent emergence of large language models (LLMs), particularly their chain-of-thought (CoT) reasoning capabilities, offers promising opportunities for developing relevance systems that are both more interpretable and more robust. However, existing training paradigms have notable limitations: SFT and DPO suffer from poor generalization on l…

Interesting: I was unsure if I should buy a 2nd hand OLED computer monitor for a specific price and if I really should because it's some kind of luxury for a few hundred Euros.
So I asked ChatGPT for (1) estimating a fair price given all the relevant information about that and then (2) describing my situation and letting it generate a /- list (to check if I have overseen an aspect) and a recommendation for buy/not buy.
The result was fascinating to me. One of the better use-…

#GNU findutils help:
> ‘environment is too large for exec’
>
> This message means that you have so many environment variables set (or such large values for them) that there is no room within the system-imposed limits on program command line argument length to invoke any program. This is an unlikely situation and is more likely result of an attempt to test the limits of xargs, or break it. Please try unsetting some environment variables, or exiting the current shell. You can also use ‘xargs --show-limits’ to understand the relevant sizes.
Okay, let's check:
$ xargs --show-limits
xargs: environment is too large for exec
🤦

when you just bored and hanging out with a ginger kid and a bird, but everyone think you sus.
source: https://www.metmuseum.org/art/collection/search/458982

De maneira geral, as pessoas mostram como são burras em comentšrios sobre notícias em redes sociais. Mas parece que é ainda pior quando são notícias internacionais. Fica um espírito de jogo de futebol somado a um conhecimento nulo de geopolítica. E o cidadão médio parece entender ainda menos de geopolítica do que das outras coisas. Mesmo pessoas que costumam tecer comentšrios relevantes em política nacional comumente falam muita groselha quando assunto é política internacional.

Retentive Relevance: Capturing Long-Term User Value in Recommendation Systems
Saeideh Bakhshi, Phuong Mai Nguyen, Robert Schiller, Tiantian Xu, Pawan Kodandapani, Andrew Levine, Cayman Simpson, Qifan Wang
https://arxiv.org/abs/2510.07621

Retentive Relevance: Capturing Long-Term User Value in Recommendation Systems
Recommendation systems have traditionally relied on short-term engagement signals, such as clicks and likes, to personalize content. However, these signals are often noisy, sparse, and insufficient for capturing long-term user satisfaction and retention. We introduce Retentive Relevance, a novel content-level survey-based feedback measure that directly assesses users' intent to return to the platform for similar content. Unlike other survey measures that focus on immediate satisfaction, Retenti…

Morning all! Heading out to run a workshop on emotions and emotional regulation this morning. One of my favourite topics.
Then *finally* getting to see the physio about my nagging back pain. And yes, emotions are relevant there too! 🤣

Value bounds and Convergence Analysis for Averages of LRP attributions
Alexander Binder, Nastaran Takmil-Homayouni, Urun Dogan
https://arxiv.org/abs/2509.08963 https://

Value bounds and Convergence Analysis for Averages of LRP attributions
We analyze numerical properties of Layer-wise relevance propagation (LRP)-type attribution methods by representing them as a product of modified gradient matrices. This representation creates an analogy to matrix multiplications of Jacobi-matrices which arise from the chain rule of differentiation. In order to shed light on the distribution of attribution values, we derive upper bounds for singular values. Furthermore we derive component-wise bounds for attribution map values. As a main result,…

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance
Jianhui Yang, Yiming Jin, Pengkun Jiao, Chenhe Dong, Zerui Huang, Shaowei Yao, Xiaojiang Zhou, Dan Ou, Haihong Tang
https://arxiv.org/abs/2510.08048

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance
Query-product relevance prediction is fundamental to e-commerce search and has become even more critical in the era of AI-powered shopping, where semantic understanding and complex reasoning directly shape the user experience and business conversion. Large Language Models (LLMs) enable generative, reasoning-based approaches, typically aligned via supervised fine-tuning (SFT) or preference optimization methods like Direct Preference Optimization (DPO). However, the increasing complexity of busin…