Ax Ellie Y. Cheng, Logan Weber, Tian Jin, Michael Carbin 3/18/2026

Sharing State Between Prompts and Programs

Programming abstraction for shared state between prompts and programs, enabling interoperability between natural language and traditional programming with LLMs.

Ax Ignacio Heredia, \'Alvaro L\'opez Garc\'ia, Fernando Aguilar G\'omez, Diego Aguirre, Caterina Alarc\'on Mar\'in, Khadijeh Alibabaei, Lisana Berberi, Miguel Caballer, Amanda Calatrava, Pedro Castro, Alessandro Costantini, Mario David, Jaime D\'iez Stefan Dlugolinsky, Borja Esteban Sanchis, Giacinto Donvito, Leonhard Duda, Sa\'ul Fernandez, Andr\'es Heredia Canales, Valentin Kozlov, Sergio Langarita, Jo\~ao Machado, Germ\'an Molt\'o, Daniel San Mart\'in, Martin \v{S}eleng, Giang Nguyen, Marcin P{\l}\'ociennik, Marta Obreg\'on Ruiz, Susana Rebolledo Ruiz, Vicente Rodriguez, Judith S\'ainz-Pardo D\'iaz, Viet Tran 3/18/2026

AI4EOSC: a Federated Cloud Platform for Artificial Intelligence in Scientific Research

AI4EOSC federated cloud platform for AI in scientific research with reproducible ML lifecycle management across distributed e-Infrastructures.

Ax Vatsal Venkatkrishna, Indraneil Paul, Iryna Gurevych 3/18/2026

Aletheia: What Makes RLVR For Code Verifiers Tick?

Ablates RLVR pipeline components for code verifiers: intermediate thinking traces, negative samples, and on-policy training to reduce adoption cost barriers.

Ax Kai Wittenmayer, Sukrut Rao, Amin Parchami-Araghi, Bernt Schiele, Jonas Fischer 3/18/2026

CFM: Language-aligned Concept Foundation Model for Vision

CFM language-aligned concept foundation model decomposes vision model representations into human-interpretable concepts with spatial grounding for diverse downstream tasks.

Ax Magda Dubois, Cozmin Ududec, Christopher Summerfield, Lennart Luettgau 3/18/2026

Ask don't tell: Reducing sycophancy in large language models

Experimental study of sycophancy in LLMs—tendency to favor user-affirming over critical responses—with controlled interventions to identify and prevent the alignment failure.