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Our work on how LLMs store relations selected as NeurIPS Spotlight paper
Our paper The Structure of Relation Decoding Linear Operators in Large Language Models by Miranda Anna Christ, Adrián Csiszárik, Gergely Becsó, and Dániel Varga was accepted at the NeurIPS 2025 conference as a Spotlight paper (~3% of submissions).
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Healthcare

Prevention & Prediction

Patient Pathways

Patient Pathway Mission
Leveraging Hungary’s healthcare data assets for prevention, prediction, and decision support.
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MTA Inaugural Lecture: Asymptotic Behavior of Large Structures

Event
January 7, 2026
events
On January 7, 2026, Balázs Szegedy delivers his inaugural lecture at the Hungarian Academy of Sciences, exploring how limit theories of graphs and hypergraphs have reshaped our understanding of large mathematical structures. The talk highlights applications in additive combinatorics and higher-order Fourier analysis, while also connecting these concepts to dynamic systems and neural networks. You can find details here.
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January 7, 2026

Rényi AI at MTA: Artificial Intelligence through a Mathematical Lens

Event
January 5, 2026
events
On January 5, Anna Miranda Christ (UC Berkeley) presents “The Structure of Relation Decoding Linear Operators in Large Language Models” as the opening lecture of the MTA Section of Mathematics’ series on AI. Based on her NeurIPS 2025 Spotlight paper co-authored with the Rényi AI team, the talk demonstrates how LLMs encode knowledge through systems of interconnected conceptual patterns rather than isolated facts. You can find details here.
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January 5, 2026

Rényi AI at AIME25: AI-Supported Patient Journey Analysis

Event
November 27, 2025
events
At the 2025 Academia-Industry Matching Event (AIME25), held at the HUN-REN Headquarters, Dezső Miklós presented the latest results from the Rényi AI Research Group with a special focus on AI-driven healthcare innovation. The talk showcased our ongoing work in modeling the Hungarian healthcare system and developing predictive methods for understanding and forecasting patient journeys. Emphasis was placed on model interpretability and explainability—key requirements for clinical deployment—as well as our contributions to cancer screening research, including prostate and colorectal cancer.
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November 27, 2025

Rényi AI at ÁBTL conference: AI-Driven Archival Workflows in Practice

Event
November 12, 2025
events
At the open conference “The Everyday Work of State Security”, hosted at the Historical Archives of the State Security in Budapest, Rényi AI delivered a keynote presentation on its collaborative work with the Historical Archives of the Hungarian State Security and the National Archives of Hungary. The joint effort aims to accelerate archival workflows and improve the accessibility and reliability of historical collections. We introduced a trustworthy, semi-agentic Retrieval-Augmented Generation (RAG) system developed using the Council of Ministers’ meeting minutes from the first Imre Nagy government.
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November 12, 2025
The Team
The AI group at the institute brings together experts with backgrounds in both industry and academia. We place equal emphasis on theoretical foundations, thorough experimentation, and practical applications. Our close collaboration ensures a continuous exchange of knowledge between scientific research and applied projects.
All Theory Applications Former members
Balázs Szegedy
Mathematical Theory
Attila Börcs, PhD
NLP, Modeling, MLOps
Adrián Csiszárik
Representation Learning, Foundations
Győző Csóka
NLP, MLOps
Domonkos Czifra
NLP, Foundations
Botond Forrai
Modeling
Péter Kőrösi-Szabó
Modeling
Gábor Kovács
NLP, Modeling
Judit Laki, MD PhD
Healthcare
Márton Muntag
Time Series, NLP, Modeling
Dávid Terjék
Generalization, Mathematical Theory
Dániel Varga
Foundations, Computer aided proofs
Pál Zsámboki
Reinforcement Learning, Geometric Deep Learning
Zsolt Zombori
Formal Reasoning
Péter Ágoston
Combinatory, Geometry
Beatrix Mária Benkő
Representation Learning
Jakab Buda
NLP
Diego González Sánchez
Generalization, Mathematical Theory
Melinda F. Kiss
Representation Learning
Ákos Matszangosz
Topology, Foundations
Alex Olár
Foundations
Gergely Papp
Modeling
Open Positions
The Rényi AI group is actively recruiting both theorists and practitioners.
Machine Learning Engineer
Announcement: July 1, 2025
Deadline: rolling
applications
Rényi Institute is seeking Machine Learning Engineers to join our AI Research & Development team. Preferred Qualifications: • MLOps experience (especially in cloud environments) • Industry experience working on ML solutions
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Research Scientist
Announcement: July 1, 2025
Deadline: rolling
theory, applications
Rényi Institute is seeking Research Scientists to join our AI Research & Development team. You will have the privilege to work at a renowned academic institute and do what you love: do research and publish in the field of machine learning / deep learning.
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All Positions
Rényi AI - Building bridges between mathematics and artificial intelligence.