Advancing Open and Reproducible Relational Learning: RelArena- alpha, TabPFN-Rel and RPI

arXiv:2608.16319 · cs.LG · Submitted 2026-08-17 · Read on arXiv

cs.LG

Submitted: 2026-08-17

Updated: 2026-09-07

Code: https://github.com/PriorLabs/relarena

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 23× in this paper · explained in 2 episodes
• Benchmarking — 15× in this paper · explained in 3 episodes
• Foundation Model — 14× in this paper · explained in 3 episodes
• Feature Engineering — 12× in this paper · explained in 3 episodes
• Foundation Models — 10× in this paper · explained in 7 episodes
• Aggregation — 8× in this paper · explained in 1 episode
• AUC — 7× in this paper · explained in 2 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 3× in this paper
• Model-Agnostic — 3× in this paper · explained in 2 episodes
• Bayesian Optimization — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Predictive Modeling — 2× in this paper · explained in 2 episodes
• Predictive Query Language — 2× in this paper
• Provenance — 2× in this paper · explained in 3 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Unified Framework — 2× in this paper · explained in 5 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Agentic Coding — 1× in this paper · explained in 1 episode
• Data Provenance — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 1× in this paper
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• RelBench: A Benchmark for Deep Learning on Relational Databases
• 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs
• REDELEX: A Framework for Relational Deep Learning Exploration
• RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
• TabArena: A Living Benchmark for Machine Learning on Tabular Data
• RDBLearn: Simple In-Context Prediction Over Relational Databases
• No Need to Train Your RDB Foundation Model
• RelAgent: LLM Agents as Data Scientists for Relational Learning
• Parameter-Free Encoders Remain Viable for RDB Foundation Models
• RelGNN: Composite Message Passing for Relational Deep Learning
• KumoRFM-2: Scaling Foundation Models for Relational Learning
• Relational Graph Transformer
• TabPFN-3: Technical Report
• PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
• Pitfalls of Graph Neural Network Evaluation
• Relational Deep Learning: Graph Representation Learning on Relational Databases
• One button machine for automating feature engineering in relational databases
• Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases
• Scikit-learn: Machine Learning in Python
• Beyond IID: How General Are Tabular Foundation Models, Really?

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