Tootfinder

On pre-local tabularity above $\mathrm{S4}\times \mathrm{S4}$
Ilya B. Shapirovsky, Vladislav V. Sliusarev
https://arxiv.org/abs/2506.20874 https://

On pre-local tabularity above $\mathrm{S4}\times \mathrm{S4}$
We investigate pre-local tabularity in normal extensions of the logic $\mathrm{S4}\times \mathrm{S4}$. We show that there are exactly four pre-locally tabular logics in normal extensions of products of finite height, and that every non-locally tabular logic in this family is contained in one of them. We also give an axiomatic criterion of local tabularity above the logic of products with Noetherian skeletons. Then we construct examples of pre-locally tabular extensions of $\mathrm{S4}\times \ma…

Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries
Josefa Lia Stoisser, Marc Boubnovski Martell, Kaspar M\"artens, Lawrence Phillips, Stephen Michael Town, Rory Donovan-Maiye, Julien Fauqueur
https://arxiv.org/abs/2505.21801

Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries
Electronic health records (EHRs) contain richly structured, longitudinal data essential for predictive modeling, yet stringent privacy regulations (e.g., HIPAA, GDPR) often restrict access to individual-level records. We introduce Query, Don't Train (QDT): a structured-data foundation-model interface enabling tabular inference via LLM-generated SQL over EHRs. Instead of training on or accessing individual-level examples, QDT uses a large language model (LLM) as a schema-aware query planner to g…

It's Mamdani Time! -- The upside potential and downside risk of the new Democratic party. (Jonathan V. Last/The Bulwark)
https://www.thebulwark.com/p/its-zohran-mamdani-time-democratic-party-new-york
http://www.memeorandum.com/250626/p85#a250626p85

GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
Rosen Ting-Ying Yu, Cyril Picard, Faez Ahmed
https://arxiv.org/abs/2505.20685

GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
Bayesian optimization (BO) effectively optimizes expensive black-box functions but faces significant challenges in high-dimensional spaces (dimensions exceeding 100) due to the curse of dimensionality. Existing high-dimensional BO methods typically leverage low-dimensional embeddings or structural assumptions to mitigate this challenge, yet these approaches frequently incur considerable computational overhead and rigidity due to iterative surrogate retraining and fixed assumptions. To address t…

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
https://arxiv.org/abs/2507.18504

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
Large Language Models (LLMs) have shown strong potential for tabular data generation by modeling textualized feature-value pairs. However, tabular data inherently exhibits sparse feature-level dependencies, where many feature interactions are structurally insignificant. This creates a fundamental mismatch as LLMs' self-attention mechanism inevitably distributes focus across all pairs, diluting attention on critical relationships, particularly in datasets with complex dependencies or semanticall…

🇺🇦 #NowPlaying on KEXP's #AfternoonShow
Wham!:
🎵 Careless Whisper
#Wham
https://thepillarsofcreation.bandcamp.com/track/wham-careless-whisper-the-pillars-of-creation-remix
https://open.spotify.com/track/5ffN26rI0YkSS4t6M63oez

AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data
Rana Alshaikh, Israa Alghanmi, Shelan Jeawak
https://arxiv.org/abs/2507.18442 https://…

AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data
The cognitive and reasoning abilities of large language models (LLMs) have enabled remarkable progress in natural language processing. However, their performance in interpreting structured data, especially in tabular formats, remains limited. Although benchmarks for English tabular data are widely available, Arabic is still underrepresented because of the limited availability of public resources and its unique language features. To address this gap, we present AraTable, a novel and comprehensiv…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Nick Drake:
🎵 Day Is Done
#NickDrake
https://mokuhisonorities.bandcamp.com/track/day-is-done
https://open.spotify.com/track/66790TBuwlIrGxWWTVc6yl

Why the Huge Conflicts of Interest Among Trump's Epstein Team Matter (Philip Rotner/The Bulwark)
https://www.thebulwark.com/p/why-the-huge-conflicts-of-interest-trump-epstein-lawyers-bondi-blanche-ghislaine-maxwell
http://www.memeorandum.com/250725/p22#a250725p22

First Reports Are Always Wrong. The Iran Strike Is No Exception. (Mark Hertling/The Bulwark)
https://www.thebulwark.com/p/first-reports-are-always-wrong-iran-strike-nuclear-dia-intelligence-assessment
http://www.memeorandum.com/250625/p71#a250625p71