Mehdi Cherti

32 papers A* 4A 1B 2C 1Journal 20Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Detecting generalization deficits in large language and reasoning models by using natural variations in simple problems.
Trans. Mach. Learn. Res.
Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, Jenia Jitsev
2025 J jnl
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks.
CoRR
Vishaal Udandarao, Mehdi Cherti, Shyamgopal Karthik, Jenia Jitsev, Samuel Albanie, Matthias Bethge
2025 J jnl
Concept-Aware Batch Sampling Improves Language-Image Pretraining.
CoRR
Adhiraj Ghosh, Vishaal Udandarao, Thao Nguyen, Matteo Farina, Mehdi Cherti, Jenia Jitsev, Sewoong Oh, Elisa Ricci, Ludwig Schmidt, Matthias Bethge
2025 J jnl
Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data.
CoRR
Stefania L. Moroianu, Christian Bluethgen, Pierre J. Chambon, Mehdi Cherti, Jean-Benoit Delbrouck, Magdalini Paschali, Brandon Price, Judy Gichoya, Jenia Jitsev, Curtis P. Langlotz, Akshay S. Chaudhari
2025 J jnl
Scalable heliostat surface predictions from focal spots: Sim-to-Real transfer of inverse Deep Learning Raytracing.
CoRR
Jan Lewen, Max Pargmann, Jenia Jitsev, Mehdi Cherti, Robert Pitz-Paal, Daniel Maldonado Quinto
2025 J jnl
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets.
CoRR
Marianna Nezhurina, Tomer Porian, Giovanni Pucceti, Tommie Kerssies, Romain Beaumont, Mehdi Cherti, Jenia Jitsev
2024 J jnl
A Practitioner's Guide to Continual Multimodal Pretraining.
CoRR
Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier J. Hénaff, Samuel Albanie, Matthias Bethge, Zeynep Akata
2024 A* conf
A Practitioner's Guide to Real-World Continual Multimodal Pretraining.
NeurIPS
Vishaal Udandarao, Karsten Roth, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier J. Hénaff, Samuel Albanie, Zeynep Akata, Matthias Bethge
2024 J jnl
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models.
CoRR
Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, Jenia Jitsev
2024 A conf
Application-Driven Exascale: The JUPITER Benchmark Suite.
SC
Andreas Herten, Sebastian Achilles, Damian Alvarez, Jayesh Badwaik, Eric Behle, Mathis Bode, Thomas Breuer, Daniel Caviedes-Voullième, Mehdi Cherti, Adel Dabah, Salem El Sayed, Wolfgang Frings, Ana Gonzalez-Nicolas, Eric B. Gregory, Kaveh Haghighi Mood, Thorsten Hater, Jenia Jitsev, Chelsea Maria John, Jan H. Meinke, Catrin I. Meyer, Pavel Mezentsev, Jan-Oliver Mirus, Stepan Nassyr, Carolin Penke, Manoel Römmer, Ujjwal Sinha, Benedikt von St. Vieth, Olaf Stein, Estela Suarez, Dennis Willsch, Ilya Zhukov
2024 J jnl
Application-Driven Exascale: The JUPITER Benchmark Suite.
CoRR
Andreas Herten, Sebastian Achilles, Damian Alvarez, Jayesh Badwaik, Eric Behle, Mathis Bode, Thomas Breuer, Daniel Caviedes-Voullième, Mehdi Cherti, Adel Dabah, Salem El Sayed, Wolfgang Frings, Ana Gonzalez-Nicolas, Eric B. Gregory, Kaveh Haghighi Mood, Thorsten Hater, Jenia Jitsev, Chelsea Maria John, Jan H. Meinke, Catrin I. Meyer, Pavel Mezentsev, Jan-Oliver Mirus, Stepan Nassyr, Carolin Penke, Manoel Römmer, Ujjwal Sinha, Benedikt von St. Vieth, Olaf Stein, Estela Suarez, Dennis Willsch, Ilya Zhukov
2024 J jnl
Inverse Deep Learning Ray Tracing for Heliostat Surface Prediction.
CoRR
Jan Lewen, Max Pargmann, Mehdi Cherti, Jenia Jitsev, Robert Pitz-Paal, Daniel Maldonado Quinto
2023 J jnl
A Comparative Study on Generative Models for High Resolution Solar Observation Imaging.
CoRR
Mehdi Cherti, Alexander Czernik, Stefan Kesselheim, Frederic Effenberger, Jenia Jitsev
2023 A* conf
DataComp: In search of the next generation of multimodal datasets.
NeurIPS
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
2023 J jnl
DataComp: In search of the next generation of multimodal datasets.
CoRR
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
2023 A* conf
Reproducible Scaling Laws for Contrastive Language-Image Learning.
CVPR
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev
2022 B conf
Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images.
IJCNN
Mehdi Cherti, Jenia Jitsev
2022 A* conf
LAION-5B: An open large-scale dataset for training next generation image-text models.
NeurIPS
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev
2022 J jnl
LAION-5B: An open large-scale dataset for training next generation image-text models.
CoRR
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev
2022 J jnl
Reproducible scaling laws for contrastive language-image learning.
CoRR
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev
2021 J jnl
Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images.
CoRR
Mehdi Cherti, Jenia Jitsev
2021 — conf
JUWELS Booster - A Supercomputer for Large-Scale AI Research.
ISC Workshops
Stefan Kesselheim, Andreas Herten, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona, Alexander Schug, Alexandre Strube, Roshni Kamath, Martin G. Schultz, Morris Riedel, Thomas Lippert
2021 J jnl
JUWELS Booster - A Supercomputer for Large-Scale AI Research.
CoRR
Stefan Kesselheim, Andreas Herten, Kai Krajsek, Jan Ebert, Jenia Jitsev, Mehdi Cherti, Michael Langguth, Bing Gong, Scarlet Stadtler, Amirpasha Mozaffari, Gabriele Cavallaro, Rocco Sedona, Alexander Schug, Alexandre Strube, Roshni Kamath, Martin G. Schultz, Morris Riedel, Thomas Lippert
2019 J jnl
InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification.
CoRR
Léonard Boussioux, Tomás Giro-Larraz, Charles Guille-Escuret, Mehdi Cherti, Balázs Kégl
2018 — —
Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments. (Réseaux profonds génératifs pour la génération de nouveauté : fondations, métriques et expériences).
Mehdi Cherti
2018 J jnl
Spurious samples in deep generative models: bug or feature?
CoRR
Balázs Kégl, Mehdi Cherti, Akin Kazakçi
2017 — conf
De novo drug design with deep generative models : an empirical study.
ICLR (Workshop)
Mehdi Cherti, Balázs Kégl, Akin Kazakçi
2017 J jnl
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy.
CoRR
Laetitia Le, Camille Marini, Alexandre Gramfort, David Nguyen, Mehdi Cherti, Sana Tfaili, Ali Tfayli, Arlette Baillet-Guffroy, Patrice Prognon, Pierre Chaminade, Eric Caudron, Balázs Kégl
2017 B conf
Out-of-Class Novelty Generation : An Experimental Foundation.
ICTAI
Mehdi Cherti, Balázs Kégl, Akin Kazakçi
2017 — conf
Out-of-class novelty generation: an experimental foundation.
ICLR (Workshop)
Mehdi Cherti, Balázs Kégl, Akin Kazakçi
2016 C conf
Digits that are not: Generating new types through deep neural nets.
ICCC
Akin Kazakçi, Mehdi Cherti, Balázs Kégl
2016 J jnl
Digits that are not: Generating new types through deep neural nets.
CoRR
Akin Kazakçi, Mehdi Cherti, Balázs Kégl