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).

Healthcare

Prevention & Prediction

Patient Pathways

Patient Pathway Mission

Leveraging Hungary’s healthcare data assets for prevention, prediction, and decision support.

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.
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.
November 12, 2025

Rényi AI at DLM Forum Copenhagen: Semi-Agentic RAG for Archival Access

Event
November 5, 2025
events
At the DLM Forum in Copenhagen, Rényi AI presented its joint work with the Historical Archives of the Hungarian State Security and the National Archives of Hungary to speed up archival processes and make historical collections more accessible and reliable. We showcased a trustworthy, semi-agentic Retrieval-Augmented Generation (RAG) system developed on the Council of Ministers’ meeting minutes from the first Imre Nagy government. The solution combines high-quality transcriptions with the original scans and uses a hybrid search pipeline to find the most relevant sources.
November 5, 2025

Közelebb a matematikához - Kőrösi-Szabó Péter a HUN-REN Rényi Alfréd Matematikai Kutatóintézet kutatója

Podcast
October 13, 2025
podcasts
Hogyan segíthet a Mesterséges Intelligencia a Magyar Nemzeti Levéltárnak vagy az Állambiztonsági Szolgálatok Történelmi Levéltárának, és miként lehetne nagy hasznára a hazai egészségügyi rendszernek? Mi mindennel foglalkozik az AI csoport a HUN-REN Rényi Alfréd Matematikai Kutatóintézetben? - erről beszélt a műsorban Kőrösi-Szabó Péter kutató. Az interjúból az is kiderül, hogyan látja a mesterséges intelligenciát egy olyan szakember, akinek célja, kollégáival együtt, az AI jobb megértése? És milyen előnye van a kutatói munkájában annak, hogy néhány évvel ezelőtt még az alkalmazott területen dolgozott?
October 13, 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.
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.
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
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.
Rényi AI - Building bridges between mathematics and artificial intelligence.