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20232026
most citedTabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models

3 citations · 3 across the 5 of their papers we have counts for

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cs.LG2026

Zero-Shot Coordination among LLM Agents

Adrian Hayler, Shashank Reddy Chirra, Andrei Lupu +4

We study zero-shot coordination (ZSC), where independently developed agents must coordinate at test time. While ZSC has been well studied in the RL literature, far less is known ab…

cs.LG2026

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

Adrian Hayler, Klemens Flöge, Alan Arazi +44

This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we expect to accelerate researc…

cs.LG2026

DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning

Alexander D. Goldie, Zilin Wang, Adrian Hayler +17

Automating the development of machine learning algorithms has the potential to unlock new breakthroughs. However, our ability to improve and evaluate algorithm discovery systems ha…

cs.LG2025★ 3 cited

TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models

Léo Grinsztajn, Klemens Flöge, Oscar Key +23

The first tabular foundation model, TabPFN, and its successor TabPFNv2 have impacted tabular AI substantially, with dozens of methods building on it and hundreds of applications ac…

cs.LG2025

Bringing Graphs to the Table: Zero-shot Node Classification via Tabular Foundation Models

Adrian Hayler, Xingyue Huang, İsmail İlkan Ceylan +2

Graph foundation models (GFMs) have recently emerged as a promising paradigm for achieving broad generalization across various graph data. However, existing GFMs are often trained…