Tootfinder

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…

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…

Putin says Alaska agreements with Trump on Ukraine still relevant: https://benborges.xyz/2025/10/10/putin-says-alaska-agreements-with.html

Beyond More Context: How Granularity and Order Drive Code Completion Quality
Uswat Yusuf, Genevieve Caumartin, Diego Elias Costa
https://arxiv.org/abs/2510.06606 https://…

Beyond More Context: How Granularity and Order Drive Code Completion Quality
Context plays an important role in the quality of code completion, as Large Language Models (LLMs) require sufficient and relevant information to assist developers in code generation tasks. However, composing a relevant context for code completion poses challenges in large repositories: First, the limited context length of LLMs makes it impractical to include all repository files. Second, the quality of generated code is highly sensitive to noisy or irrelevant context. In this paper, we present…

Per Zufall bin ich über die #blogparade2025 gestolpert und da das Thema bei blogissimo interessant war, hab ich mal einen Beitrag geliefert. Hoffentlich #relevant

Relevant Deformations, Brane Brick Models and Triality
Mario Carcamo, Sebastian Franco, Dongwook Ghim, Georgios P. Goulas, Rak-Kyeong Seong
https://arxiv.org/abs/2510.05517 http…

Relevant Deformations, Brane Brick Models and Triality
We extend the study of relevant deformations connecting 2d (0,2) gauge theories on D1-branes probing toric Calabi-Yau 4-folds beyond pure mass deformations. The underlying geometry provides powerful insights when field-theoretic tools are still lacking. We observe that the volume of the Sasaki-Einstein base of the Calabi-Yau 4-fold grows towards the IR, signaling the relevance of deformations. We exploit the map between gauge theory fields and GLSM fields to compute scaling dimensions directly …

I was writing (a brilliant) post about something, but now I just want to say: Writing in a box in a browser-window makes the 1980's advice relevant again: *Save your draft often* ! The danger used to be MS Word crashing, now it's just switching away from the window that will destroy your nuggets of wisdom, for them never to be seen by anyone 😪

Imagine ChatGPT but instead of predicting text it just linked you to the to 3 documents most-influential on the probabilities that would have been used to predict that text.
Could even generate some info about which parts of each would have been combined how.
There would still be issues with how training data is sourced and filtered, but these could be solved by crawling normally respecting robots.txt and by paying filterers a fair wage with a more relaxed work schedule and mental health support.
The energy issues are mainly about wild future investment and wasteful query spam, not optimized present-day per-query usage.
Is this "just search?"
Yes, but it would have some advantages for a lot of use cases, mainly in synthesizing results across multiple documents and in leveraging a language model more fully to find relevant stuff.
When we talk about the harms of current corporate LLMs, the opportunity cost of NOT building things like this is part of that.
The equivalent for art would have been so amazing too! "Here are some artists that can do what you want, with examples pulled from their portfolios."
It would be a really cool coding assistant that I'd actually encourage my students to use (with some guidelines).
#AI #GenAI #LLMs

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…