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ORCIDJenia Jitsev
Person information
- affiliation: LAION, Hamburg, Germany
- affiliation: Jülich Supercomputing Center (JSC), Germany
- affiliation: Research Center Jülich (FZJ), Germany
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2020 – today
- 2025
[c23]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al.:
Language models scale reliably with over-training and on downstream tasks. ICLR 2025- [i30]Christoph Schuhmann, Gollam Rabby, Ameya Prabhu, Tawsif Ahmed, Andreas Hochlehnert, Huu Nguyen, Nick Akinci Heidrich, Ludwig Schmidt, Robert Kaczmarczyk, Sören Auer, Jenia Jitsev, Matthias Bethge:
Project Alexandria: Towards Freeing Scientific Knowledge from Copyright Burdens via LLMs. CoRR abs/2502.19413 (2025) - [i29]Jan Lewen, Max Pargmann, Jenia Jitsev, Mehdi Cherti, Robert Pitz-Paal, Daniel Maldonado Quinto:
Scalable heliostat surface predictions from focal spots: Sim-to-Real transfer of inverse Deep Learning Raytracing. CoRR abs/2504.03712 (2025) - [i28]Jörg K. H. Franke, Urs Spiegelhalter, Marianna Nezhurina, Jenia Jitsev, Frank Hutter, Michael Hefenbrock:
Learning in Compact Spaces with Approximately Normalized Transformers. CoRR abs/2505.22014 (2025) - [i27]Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer
, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt:
OpenThoughts: Data Recipes for Reasoning Models. CoRR abs/2506.04178 (2025) - [i26]Marianna Nezhurina, Tomer Porian, Giovanni Pucceti, Tommie Kerssies, Romain Beaumont, Mehdi Cherti, Jenia Jitsev:
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets. CoRR abs/2506.04598 (2025) - [i25]Vishaal Udandarao, Mehdi Cherti, Shyamgopal Karthik, Jenia Jitsev, Samuel Albanie, Matthias Bethge:
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks. CoRR abs/2506.08227 (2025) - [i24]Lucia Cipolina-Kun, Marianna Nezhurina, Jenia Jitsev:
Game Reasoning Arena: A Framework and Benchmark for Assessing Reasoning Capabilities of Large Language Models via Game Play. CoRR abs/2508.03368 (2025) - [i23]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:
Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data. CoRR abs/2508.16783 (2025) - [i22]Marianna Nezhurina, Jörg K. H. Franke, Taishi Nakamura, Timur Carstensen, Niccolò Ajroldi, Ville Komulainen, David Salinas, Jenia Jitsev:
Open-sci-ref-0.01: open and reproducible reference baselines for language model and dataset comparison. CoRR abs/2509.09009 (2025) - [i21]Huu Nguyen, Victor May, Harsh Raj, Marianna Nezhurina, Yishan Wang, Yanqi Luo, Minh Chien Vu, Taishi Nakamura, Ken Tsui, Van Khue Nguyen, David Salinas, Aleksandra Krasnodebska, Christoph Schuhmann, Mats Leon Richter, Xuan-Son Vu, Jenia Jitsev:
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources. CoRR abs/2509.25531 (2025) - [i20]Adhiraj Ghosh, Vishaal Udandarao, Thao Nguyen, Matteo Farina, Mehdi Cherti, Jenia Jitsev, Sewoong Oh, Elisa Ricci, Ludwig Schmidt, Matthias Bethge:
Concept-Aware Batch Sampling Improves Language-Image Pretraining. CoRR abs/2511.20643 (2025) - 2024
- [c22]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. NeurIPS 2024 - [c21]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. NeurIPS 2024 - [c20]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:
Application-Driven Exascale: The JUPITER Benchmark Suite. SC 2024: 32 - [i19]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024) - [i18]Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, Jenia Jitsev:
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models. CoRR abs/2406.02061 (2024) - [i17]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i16]Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon:
Resolving Discrepancies in Compute-Optimal Scaling of Language Models. CoRR abs/2406.19146 (2024) - [i15]Jan Lewen, Max Pargmann, Mehdi Cherti, Jenia Jitsev, Robert Pitz-Paal, Daniel Maldonado Quinto:
Inverse Deep Learning Ray Tracing for Heliostat Surface Prediction. CoRR abs/2408.10802 (2024) - [i14]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:
Application-Driven Exascale: The JUPITER Benchmark Suite. CoRR abs/2408.17211 (2024) - 2023
- [c19]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible Scaling Laws for Contrastive Language-Image Learning. CVPR 2023: 2818-2829 - [c18]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:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [i13]Mehdi Cherti, Alexander Czernik, Stefan Kesselheim, Frederic Effenberger, Jenia Jitsev:
A Comparative Study on Generative Models for High Resolution Solar Observation Imaging. CoRR abs/2304.07169 (2023) - [i12]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:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i11]Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, Ludwig Schmidt:
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. CoRR abs/2308.01390 (2023) - 2022
- [j4]Jose M. Clavijo, Paul Glaysher, Jenia Jitsev, Judith M. Katzy:
Adversarial domain adaptation to reduce sample bias of a high energy physics event classifier *. Mach. Learn. Sci. Technol. 3(1): 15014 (2022) - [c17]Mehdi Cherti, Jenia Jitsev:
Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images. IJCNN 2022: 1-9 - [c16]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:
LAION-5B: An open large-scale dataset for training next generation image-text models. NeurIPS 2022 - [i10]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:
LAION-5B: An open large-scale dataset for training next generation image-text models. CoRR abs/2210.08402 (2022) - [i9]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning. CoRR abs/2210.16110 (2022) - [i8]Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, Jenia Jitsev:
Reproducible scaling laws for contrastive language-image learning. CoRR abs/2212.07143 (2022) - 2021
- [c15]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:
JUWELS Booster - A Supercomputer for Large-Scale AI Research. ISC Workshops 2021: 453-468 - [i7]Marcel Aach, Jens Henrik Göbbert, Jenia Jitsev:
Generalization over different cellular automata rules learned by a deep feed-forward neural network. CoRR abs/2103.14886 (2021) - [i6]Mehdi Cherti, Jenia Jitsev:
Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images. CoRR abs/2106.00116 (2021) - [i5]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:
JUWELS Booster - A Supercomputer for Large-Scale AI Research. CoRR abs/2108.11976 (2021) - [i4]Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, Aran Komatsuzaki:
LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs. CoRR abs/2111.02114 (2021) - 2020
- [c14]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoG 2020: 447-454 - [c13]Run Zhang, Gabriele Cavallaro, Jenia Jitsev:
Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning. IGARSS 2020: 617-620 - [c12]Rocco Sedona, Gabriele Cavallaro, Jenia Jitsev, Alexandre Strube, Morris Riedel, Matthias Book:
Scaling Up a Multispectral Resnet-50 to 128 GPUs. IGARSS 2020: 1058-1061 - [c11]Mario Rüttgers, Seong-Ryong Koh, Jenia Jitsev, Wolfgang Schröder, Andreas Lintermann:
Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning. ISC Workshops 2020: 81-101 - [i3]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoRR abs/2004.00567 (2020)
2010 – 2019
- 2019
- [j3]Rocco Sedona, Gabriele Cavallaro, Jenia Jitsev, Alexandre Strube, Morris Riedel, Jón Atli Benediktsson:
Remote Sensing Big Data Classification with High Performance Distributed Deep Learning. Remote. Sens. 11(24): 3056 (2019) - [i2]Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, Jenia Jitsev, Heinz Pitsch:
Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows. CoRR abs/1911.11380 (2019) - 2018
- [c10]Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch:
Towards Prediction of Turbulent Flows at High Reynolds Numbers Using High Performance Computing Data and Deep Learning. ISC Workshops 2018: 614-623 - 2014
- [c9]Jenia Jitsev:
Self-generated Off-line Memory Reprocessing Strongly Improves Generalization in a Hierarchical Recurrent Neural Network. ICANN 2014: 659-666 - 2012
- [c8]Jenia Jitsev, Nobi Abraham, Abigail Morrison, Marc Tittgemeyer:
Learning from Delayed Reward und Punishment in a Spiking Neural Network Model of Basal Ganglia with Opposing D1/D2 Plasticity. ICANN (1) 2012: 459-466 - [c7]Jenia Jitsev, Abigail Morrison, Marc Tittgemeyer:
Learning from positive and negative rewards in a spiking neural network model of basal ganglia. IJCNN 2012: 1-8 - 2011
- [j2]Nico S. Gorbach, Christoph Schütte, Corina Melzer, Mathias Goldau, Olivia Sujazow, Jenia Jitsev, Tania S. Douglas, Marc Tittgemeyer:
Hierarchical Information-Based Clustering for Connectivity-Based Cortex Parcellation. Frontiers Neuroinformatics 5: 18 (2011) - [c6]Yasuomi D. Sato, Jenia Jitsev, Jörg Bornschein, Daniela Pamplona, Christian Keck, Christoph von der Malsburg:
A Gabor Wavelet Pyramid-Based Object Detection Algorithm. ISNN (2) 2011: 232-240 - [c5]Nico S. Gorbach, Silvan Siep, Jenia Jitsev, Corina Melzer, Marc Tittgemeyer:
Information-Theoretic Connectivity-Based Cortex Parcellation. MLINI 2011: 186-193 - 2010
- [c4]Yasuomi D. Sato, Jenia Jitsev, Christoph von der Malsburg:
Visual Object Detection by Specifying the Scale and Rotation Transformations. ICONIP (2) 2010: 616-624 - [c3]Jenia Jitsev, Christoph von der Malsburg:
Off-line memory reprocessing following on-line unsupervised learning strongly improves recognition performance in a hierarchical visual memory. IJCNN 2010: 1-8 - [c2]Yasuomi D. Sato, Jenia Jitsev, Thomas Burwick, Christoph von der Malsburg:
Dynamic link models for global decision making with binding-by-synchrony. NaBIC 2010: 201-208
2000 – 2009
- 2009
- [j1]Jenia Jitsev, Christoph von der Malsburg:
Experience-driven formation of parts-based representations in a model of layered visual memory. Frontiers Comput. Neurosci. 3: 15 (2009) - [i1]Jenia Jitsev, Christoph von der Malsburg:
Experience-driven formation of parts-based representations in a model of layered visual memory. CoRR abs/0905.2125 (2009) - 2008
- [c1]Yasuomi D. Sato, Jenia Jitsev, Christoph von der Malsburg:
A Visual Object Recognition System Invariant to Scale and Rotation. ICANN (1) 2008: 991-1000
Coauthor Index
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