49 citations · 50 across the 7 of their papers we have counts for
7 papers
Statistically Indistinguishable, Operationally Distinct: A Formal Barrier for Tabular Foundation Models
Tassilo Klein, Johannes Hoffart
Tabular foundation models cannot reason about data produced by running systems without access to the rules that govern them. We make this statement falsifiable. The \emph{Operation…
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Vignesh Kothapalli, Rishabh Ranjan, Valter Hudovernik +4
Relational Foundation Models (RFMs) facilitate data-driven decision-making by learning from complex multi-table databases. However, the diverse relational databases needed to train…
SALT-KG: A Benchmark for Semantics-Aware Learning on Enterprise Tables
Isaiah Onando Mulang, Felix Sasaki, Tassilo Klein +3
Building upon the SALT benchmark for relational prediction (Klein et al., 2024), we introduce SALT-KG, a benchmark for semantics-aware learning on enterprise tables. SALT-KG extend…
Position: Foundation Models for Tabular Data within Systemic Contexts Need Grounding
Tassilo Klein, Johannes Hoffart
This position paper argues that foundation models for tabular data face inherent limitations when isolated from operational context - the procedural logic, declarative rules, and d…
SALT: Sales Autocompletion Linked Business Tables Dataset
Tassilo Klein, Clemens Biehl, Margarida Costa +3
Foundation models, particularly those that incorporate Transformer architectures, have demonstrated exceptional performance in domains such as natural language processing and image…
PORTAL: Scalable Tabular Foundation Models via Content-Specific Tokenization
Marco Spinaci, Marek Polewczyk, Johannes Hoffart +3
Self-supervised learning on tabular data seeks to apply advances from natural language and image domains to the diverse domain of tables. However, current techniques often struggle…
Large Process Models: A Vision for Business Process Management in the Age of Generative AI
Timotheus Kampik, Christian Warmuth, Adrian Rebmann +12
The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over…