Publications & Preprints

Publications & preprints that have benefited from Small & Large Grants include:​

1. Georgios Vlassis, Saleh Ashkboos, Alexandra Volkova, Torsten Hoefler, Dan Alistarh. “Beyond outliers: A study of optimizers under quantization”. arXiv preprint arXiv:2509.23500 (2025).

2. Andrei Panferov, Erik Schultheis, Soroush Tabesh, Dan Alistarh. “Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation”. Under submission, arxiv preprint arXiv:2601.22813 (2026).

3. Wenckstern, J., Jain, E., Cheng, Y., von Querfurth, B., Vasilev, K., Pariset, M., Cheng, P. F., Let al. “AI-powered virtual tissues from spatial proteomics for clinical diagnostics and biomedical discovery. In Revision at Nature”. Best Paper Award at ICLR’25 MLGenX Workshop (2025).

4. von Querfurth, B., Klein, L., Vincent-Cuaz, C., Jain, E., Cheng, Y., Wenckstern, J., Cheng, P. F., et al. “A multimodal foundation model for tissue proteomics and morphology in cancer”. In Review at Nature Biotechnology (2026).

5. Vasilev, K., Misrahi, A., Jain, E., Cheng, P. F., Liakopoulos, P., Michielin, O., ... & Bunne, C. “MTBBench: A Multimodal Sequential Clinical Decision-Making Benchmark in Oncology. In Advances in Neural Information Processing Systems (NeurIPS) Dataset and Benchmarks Track”. Invited for an Editorial at European Society for Medical Oncology (ESMO) Annals of Oncology (2025).

6. Wenteler, A., Klein, L., von Querfurth, B., Wenckstern, J., Epiney, J., Cairoli, A., Santamaria-Martínez, A., Oricchio, E., & Bunne, C. “Foundation Model-based Simulation of Spatiotemporal Tissue Responses to Therapy”. In Submission at International Conference of Machine Learning (ICML) (2026).

7. Adamov, Simon, Joel Oskarsson, Leif Denby, Tomas Landelius, Kasper Hintz, Simon Christiansen, Irene Schicker et al. "Building machine learning limited area models: kilometer-scale weather forecasting in realistic settings." arXiv preprint arXiv:2504.09340 (2025).

8. Lehmann, Fanny, Firat Ozdemir, Benedikt Soja, Torsten Hoefler, Siddhartha Mishra, and Sebastian Schemm. "Finetuning a weather foundation model with lightweight decoders for unseen physical processes." arXiv preprint arXiv:2506.19088 (2025).

9. Yutong Chen, Yiming Wang,  Xucong Zhang, Sergey Prokudin, and Siyu Tang. "GGPT: Geometry-Grounded Point Transformer." CVPR (2026).

10. McGinnis, Julian, Suprosanna Shit, Florian A. Hölzl, Paul Friedrich, Paul Büschl, Vasiliki Sideri-Lampretsa, Mark Mühlau, Philippe C. Cattin, Bjoern Menze, Daniel Rueckert, and Benedikt Wiestler. “Beyond Uniformity: Regularizing Implicit Neural Representations through a Lipschitz Lens.” International Conference on Learning Representations (ICLR) 2026.

11. Laguna, Sonia, Andrea Agostini, Alain Ryser, Samuel Ruiperez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, et al. “Structure Is Supervision: Multiview Masked Autoencoders for Radiology.” arXiv preprint arXiv:2511.22294 (2025).

12. Böhi, Simon, Irene Cannistraci, Sergio Muñoz Gonzalez, Moritz Vandenhirtz, Sonia Laguna, Samuel Ruiperez-Campillo, Max Krähenmann, Andrea Agostini, Ece Ozkan, Thomas M. Sutter, and Julia E. Vogt. “Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography.” ICLR 2026 Workshop on Foundation Models for Science (FM4Science) (2026).

13. Bran, Andres M., Tong Xie, Shai Pranesh, Jeffrey Meng, Xuan Vu Nguyen, Jeremy Goumaz, David Ming Segura et al. "MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models." arXiv preprint arXiv:2512.21231 (2025).

14. Yu, Y., Huang, L., Calotoiu, A. and Hoefler, T. “Scaling Laws of Global Weather Models”. arXiv preprint arXiv:2602.22962 (2026).

15. Huang, Langwen, Luigi Fusco, Florian Scheidl, Jan Zibell, Michael Armand Sprenger, Sebastian Schemm, and Torsten Hoefler. "Error bounded compression for weather and climate applications." arXiv preprint arXiv:2510.22265 (2026).

16. M Mekkattu, MY Michelis, RK Katzschmann. “SORS: A Modular, High-Fidelity Simulator for Soft Robots.” arXiv preprint arXiv:2512.15994 (2025).

17. H Zheng, B Sukhija, C Li, K Iten, A Krause, RK Katzschmann. “Learning Soft Robotic Dynamics with Active Exploration.” arXiv preprint arXiv:2510.27428 (2025).

18. E Bauer, E Nava, RK Katzschmann. “Latent action diffusion for cross-embodiment manipulation.” arXiv preprint arXiv:2506.14608 (2025).

19. E Nava, V Montesinos, E Bauer, B Forrai, J Pai, S Weirich, SD Gravert, et al. “mimic-one: a Scalable Model Recipe for General Purpose Robot Dexterity.” arXiv preprint arXiv:2506.11916 (2025).

20. Li, Gen, Yutong Chen, Yiqian Wu, Kaifeng Zhao, Marc Pollefeys, and Siyu Tang. “EgoM2P: Egocentric Multimodal Multitask Pretraining.” arXiv preprint arXiv:2506.07886 (2025).

21. Antoine Chaffin, Luca Arnaboldi, Amélie Chatelain, et al. “ColBERT-Zero: To Pre-train Or Not To Pre-train ColBERT Models.” arXiv preprint arXiv:2602.16609 (2026).

22. Wanyun Xie, Francesco Tonin, and Volkan Cevher. “MaD-Mix: Multi-Modal Data Mixtures via Latent Space Coupling for Vision-Language Model Training.” arXiv preprint arXiv:2602.07790 (2026).

23. Alexandra Volkova, Mher Safaryan, Christoph H. Lampert, et al. “Towards Robust Scaling Laws for Optimizers.” arXiv preprint arXiv:2602.07712 (2026).

24. Adam Barla, Emanuele Nevali, Luca Viano, and Volkan Cevher. “Provably Avoiding Over-Optimization in Direct Preference Optimization without Knowing the Data Distribution.” arXiv preprint arXiv:2602.06239 (2026).

25. Aavash Chhetri, Bibek Niroula, Pratik Shrestha, et al. “Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare.” arXiv preprint arXiv:2602.04416 (2026).

26. Luciano Loris Viteritti, Riccardo Rende, Subir Sachdev, and Giuseppe Carleo. “Approaching the Thermodynamic Limit with Neural-Network Quantum States.” arXiv preprint arXiv:2602.02665 (2026).

27. Manthan Patel, Jonas Frey, Mayank Mittal, et al. “DeFM: Learning Foundation Representations from Depth for Robotics.” arXiv preprint arXiv:2601.18923 (2026).

28. Zhiyin Qian, Siwei Zhang, Bharat Lal Bhatnagar, et al. “Masked Modeling for Human Motion Recovery Under Occlusions.” arXiv preprint arXiv:2601.16079 (2026).

29. Ahmad Rahimi, Valentin Gerard, Eloi Zablocki, et al. “MAD: Motion Appearance Decoupling for Efficient Driving World Models.” arXiv preprint arXiv:2601.09452 (2026).

30. Vignesh Gopakumar, Ander Gray, Joel Oskarsson, et al. “Uncertainty Quantification of Surrogate Models Using Conformal Prediction.” arXiv preprint arXiv:2408.09881 (2026).

31. Yuanwen Yue, Damien Robert, Jianyuan Wang, et al. “LitePT: Lighter Yet Stronger Point Transformer.” arXiv preprint arXiv:2512.13689 (2025).

32. Benjamin Gundersen, Nicolas Deperrois, Samuel Ruiperez-Campillo, et al. “Enhancing Radiology Report Generation and Visual Grounding Using Reinforcement Learning.” arXiv preprint arXiv:2512.10691 (2025).

33. Ana-Maria Cretu, Klim Kireev, Amro Abdalla, et al. “Evaluating Concept Filtering Defenses against Child Sexual Abuse Material Generation by Text-to-Image Models.” arXiv preprint arXiv:2512.05707 (2025).

34. Thomas Pethick, Kimon Antonakopoulos, Antonio Silveti-Falls, et al. “Training Neural Networks at Any Scale.” arXiv preprint arXiv:2511.11163 (2025).

35. Botao Ye, Boqi Chen, Haofei Xu, et al. “YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting.” arXiv preprint arXiv:2511.07321 (2025).

36. Negar Foroutan, Paul Teiletche, Ayush Kumar Tarun, et al. “Revisiting Multilingual Data Mixtures in Language Model Pretraining.” arXiv preprint arXiv:2510.25947 (2025).

37. Pablo Acuaviva, Aram Davtyan, Mariam Hassan, et al. “Rethinking Visual Intelligence: Insights from Video Pretraining.” arXiv preprint arXiv:2510.24448 (2025).

38. Giovanni De Muri, Mark Vero, Robin Staab, et al. “Pay Attention to the Triggers: Constructing Backdoors That Survive Distillation.” arXiv preprint arXiv:2510.18541 (2025).

39. Yasaman Haghighi, Bastien van Delft, Mariam Hassan, et al. “LayerSync: Self-Aligning Intermediate Layers.” arXiv preprint arXiv:2510.12581 (2025).

40. Wuyang Li, Wentao Pan, Po-Chien Luan, et al. “Stable Video Infinity: Infinite-Length Video Generation with Error Recycling.” arXiv preprint arXiv:2510.09212 (2025).

41. Kazuki Egashira, Robin Staab, Thibaud Gloaguen, et al. “Fewer Weights, More Problems: A Practical Attack on LLM Pruning.” arXiv preprint arXiv:2510.07985 (2025).

42. Morteza Rohanian and Michael Krauthammer. “Optimizing Speech Language Models for Acoustic Consistency.” arXiv preprint arXiv:2509.26276 (2025).

43. Apertus Project, Alejandro Hernández-Cano, Alexander Hägele, et al. “Apertus: Democratizing Open and Compliant LLMs for Global Language Environments.” arXiv preprint arXiv:2509.14233 (2025).

44. Andrew Jreissaty, Hang Zhang, Jairo C. Quijano, et al. “Entanglement and Optimization within Autoregressive Neural Quantum States.” arXiv preprint arXiv:2509.12365 (2025).

45. Maciej Besta, Shriram Chandran, Robert Gerstenberger, et al. “Psychologically Enhanced AI Agents.” arXiv preprint arXiv:2509.04343 (2025).

46. Andrei Semenov, Matteo Pagliardini, and Martin Jaggi. “Benchmarking Optimizers for Large Language Model Pretraining.” arXiv preprint arXiv:2509.01440 (2025).

47. Frano Rajić, Haofei Xu, Marko Mihajlovic, et al. “Multi-View 3D Point Tracking.” arXiv preprint arXiv:2508.21060 (2025).

48. Negar Foroutan, Clara Meister, Debjit Paul, et al. “Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization.” arXiv preprint arXiv:2508.04796 (2025).

49. Yung-Hsu Yang, Luigi Piccinelli, Mattia Segu, et al. “3D-MOOD: Lifting 2D to 3D for Monocular Open-Set Object Detection.” arXiv preprint arXiv:2507.23567 (2025).

50. Simon Matrenok, Skander Moalla, and Caglar Gulcehre. “Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions.” arXiv preprint arXiv:2507.08068 (2025).

51. Maxime Martinasso, Mark Klein, and Thomas C. Schulthess. “Alps: A Versatile Research Infrastructure.” arXiv preprint arXiv:2507.02404 (2025).

52. Rahul Ramachandran, Ali Garjani, Roman Bachmann, et al. “How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks.” arXiv preprint arXiv:2507.01955 (2025).

53. Stefano Schuppli, Fawzi Mohamed, Henrique Mendonça, et al. “Evolving HPC Services to Enable ML Workloads on HPE Cray EX.” arXiv preprint arXiv:2507.01880 (2025).

54. Andrea Agostini, Sonia Laguna, Alain Ryser, et al. “Leveraging the Structure of Medical Data for Improved Representation Learning.” arXiv preprint arXiv:2507.02987 (2025).

55. Negar Foroutan, Jakhongir Saydaliev, Ye Eun Kim, et al. “ConLID: Supervised Contrastive Learning for Low-Resource Language Identification.” arXiv preprint arXiv:2506.15304 (2025).

56. Samuel Simko, Mrinmaya Sachan, Bernhard Schölkopf, et al. “Improving Large Language Model Safety with Contrastive Representation Learning.” arXiv preprint arXiv:2506.11938 (2025).

57. Klim Kireev, Ana-Maria Cretu, Raphael Meier, et al. “A Manually Annotated Image-Caption Dataset for Detecting Children in the Wild.” arXiv preprint arXiv:2506.10117 (2025).

58. Pablo Acuaviva, Aram Davtyan, Mariam Hassan, et al. “From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models.” arXiv preprint arXiv:2506.07280 (2025).

59. Elias Abad Rocamora, Christian Schlarmann, Naman Deep Singh, et al. “Robustness in Both Domains: CLIP Needs a Robust Text Encoder.” arXiv preprint arXiv:2506.03355 (2025).

60. Kai Lion, Liang Zhang, Bingcong Li, Niao He. “PoLAR: Polar-Decomposed Low-Rank Adapter Representation.” arXiv preprint arXiv:2506.03133 (2025).

61. Thomas Pethick, Wanyun Xie, Mete Erdogan, et al. “Generalized Gradient Norm Clipping & Non-Euclidean (L₀, L₁)-Smoothness.” arXiv preprint arXiv:2506.01913 (2025).

62. Wanyun Xie, Francesco Tonin, and Volkan Cevher. “Chameleon: A Flexible Data-Mixing Framework for Language Model Pretraining and Finetuning.” arXiv preprint arXiv:2505.24844 (2025).

63. Alejandro Hernández-Cano, Dhia Garbaya, Imanol Schlag, et al. “Towards Fully FP8 GEMM LLM Training at Scale.” arXiv preprint arXiv:2505.20524 (2025).

64. Dongyang Fan, Vinko Sabolčec, and Martin Jaggi. “URLs Help, Topics Guide: Understanding Metadata Utility in LLM Training.” arXiv preprint arXiv:2505.16570 (2025).

65. Roberto L. Castro, Andrei Panferov, Soroush Tabesh, et al. “Quartet: Native FP4 Training Can Be Optimal for Large Language Models.” arXiv preprint arXiv:2505.14669 (2025).

66. Yixuan Xu, Antoni-Joan Solergibert i Llaquet, Antoine Bosselut, et al. “Positional Fragility in LLMs: How Offset Effects Reshape Our Understanding of Memorization Risks.” arXiv preprint arXiv:2505.13171 (2025).

67. Foteini Strati, Zhendong Zhang, George Manos, et al. “Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters.” arXiv preprint arXiv:2504.17096 (2025).

68. Dongyang Fan, Vinko Sabolčec, Matin Ansaripour, et al. “Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs.” arXiv preprint arXiv:2504.06219 (2025).

69. Alexey Gavryushin, Xi Wang, Robert J. S. Malate, et al. “MAPLE: Encoding Dexterous Robotic Manipulation Priors Learned from Egocentric Videos.” arXiv preprint arXiv:2504.06084 (2025).

70. Artyom Gadetsky, Andrei Atanov, Yulun Jiang, et al. “Large (Vision) Language Models Are Unsupervised In-Context Learners.” arXiv preprint arXiv:2504.02349 (2025).

71. Tobias Fischer, Samuel Rota Bulò, Yung-Hsu Yang, Nikhil Keetha, Lorenzo Porzi, Norman Müller, Katja Schwarz, Jonathon Luiten, Marc Pollefeys, Peter Kontschieder. “FlowR: Flowing from Sparse to Dense 3D Reconstructions.” arXiv preprint arXiv:2504.01647 (2025).

72. Boqi Chen, Cédric Vincent-Cuaz, Lydia A. Schoenpflug, et al. “Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology.” arXiv preprint arXiv:2503.18709 (2025).

73. Maximilian Böther, Xiaozhe Yao, Tolga Kerimoglu, et al. “Mixtera: A Data Plane for Foundation Model Training.” arXiv preprint arXiv:2502.19790 (2025).

74. Roman Bachmann, Jesse Allardice, David Mizrahi, et al. “FlexTok: Resampling Images into 1D Token Sequences of Flexible Length.” arXiv preprint arXiv:2502.13967 (2025).

75. Bettina Messmer, Vinko Sabolčec, and Martin Jaggi. “Enhancing Multilingual LLM Pretraining with Model-Based Data Selection.” arXiv preprint arXiv:2502.10361 (2025).

76. Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos, et al. “Training Deep Learning Models with Norm-Constrained LMOs.” arXiv preprint arXiv:2502.07529 (2025).

77. Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruipérez-Campillo, et al. “RadVLM: A Multitask Conversational Vision-Language Model for Radiology.” arXiv preprint arXiv:2502.03333 (2025).

78. Youhe Jiang, Fangcheng Fu, Xiaozhe Yao, et al. “Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs.” arXiv preprint arXiv:2502.00722 (2025).

79. Nikola Zubić and Davide Scaramuzza. “GG-SSMs: Graph-Generating State Space Models.” arXiv preprint arXiv:2412.12423 (2025).

80. Mariam Hassan, Sebastian Stapf, Ahmad Rahimi, et al. “GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control.” arXiv preprint arXiv:2412.11198 (2024).

81. Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al. “INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge.” arXiv preprint arXiv:2411.19799 (2024).

82. Manuel Burger, Fedor Sergeev, Malte Londschien, et al. “Towards Foundation Models for Critical Care Time Series.” arXiv preprint arXiv:2411.16346 (2024).

83. Allen Hao Huang and Imanol Schlag. “Deriving Activation Functions Using Integration.” arXiv preprint arXiv:2411.13010 (2025).

84. Yutong Chen, Marko Mihajlovic, Xiyi Chen, et al. “SplatFormer: Point Transformer for Robust 3D Gaussian Splatting.” arXiv preprint arXiv:2411.06390 (2025).

85. Justin Deschenaux and Caglar Gulcehre. “Beyond Autoregression: Fast LLMs via Self-Distillation Through Time.” arXiv preprint arXiv:2410.21035 (2025).

86. Haofei Xu, Songyou Peng, Fangjinhua Wang, et al. “DepthSplat: Connecting Gaussian Splatting and Depth.” arXiv preprint arXiv:2410.13862 (2025).

87. Roberto Molinaro, Samuel Lanthaler, Bogdan Raonić, et al. “Generative AI for Fast and Accurate Statistical Computation of Fluids.” arXiv preprint arXiv:2409.18359 (2025).

88. Gerd Kortemeyer. “Tailoring Chatbots for Higher Education: Some Insights and Experiences.” arXiv preprint arXiv:2409.06717 (2025).

89. Maciej Besta, Florian Scheidl, Lukas Gianinazzi, et al. “Demystifying Higher-Order Graph Neural Networks.” arXiv preprint arXiv:2406.12841 (2025).

90. Matthias Stuermer. “Technological Perspective on Digital Sovereignty.” arXiv preprint arXiv:2406.03266 (2024).

91. Bobby He, Lorenzo Noci, Daniele Paliotta, et al. “Understanding and Minimising Outlier Features in Neural Network Training.” arXiv preprint arXiv:2405.19279 (2024).

92. Till Dieminger, Saúl Alonso-Monsalve, Christoph Alt, Claudio Bruschini, Noemi Bührer, Edoardo Charbon, Kodai Kaneyasu, Tim Weber, Matthew Franks, Davide Sgalaberna, "An ultrafast plenoptic-camera system for high-resolution 3D particle tracking in unsegmented scintillators." Accepted for publication in Nature Communications (2026).

93. S. Alonso-Monsalve, C. Cavanagh, F. Cufino, U. Kose, A. Masciellani, A. Rubbia, D. Sgalaberna, et al. "The FASERCal Conceptual Design Report - An electronic highly segmented 3D voxels plastic scintillator calorimeter with rear calorimeters and magnetic muon spectrometer." CERN-FASER-NOTE-2026-004, URL: http://cds.cern.ch/record/2954673 (2026).

94. Wang, Yiming, et al. "BulletTime: Decoupled Control of Time and Camera Pose for Video Generation." arXiv preprint arXiv:2512.05076 (2025).

95. Fedele, Elisabetta, Boyang Sun, Leonidas Guibas, Marc Pollefeys, and Francis Engelmann. "SuperDec: 3D Scene Decomposition with Superquadrics Primitives." In Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 24625-24635 (2025).

96. Fedele, Elisabetta, Francis Engelmann, Ian Huang, Or Litany, Marc Pollefeys, and Leonidas Guibas. "SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling". To appear in Proceedings of the International Conference on Learning Representations, ICLR (2026).

97. Project ID a03, Rong Zou, Marco Cannici, Davide Scaramuzza. “Event-Aided Sharp Radiance Field Reconstruction for Fast-Flying Drones.” IEEE Transactions on Robotics (2026). 

98. Pai, Jonas, Liam Achenbach, Victoriano Montesinos, Benedek Forrai, Oier Mees, and Elvis Nava. "mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs." arXiv preprint arXiv:2512.15692 (2025).

99. Yuhui Ding, Thomas Hofmann. "Simplifying SE(3) Protein Backbone Generation with Scaled Projection Flow". submitted to ICLML (2026).

100. Sun, Haotian, Yitong Li, Yuchen Zhuang, Niao He, Hanjun Dai, and Bo Dai. "AmorLIP: Efficient Language-Image Pretraining via Amortization." In The Thirty-ninth Annual Conference on Neural Information Processing Systems, NeurIPS (2025).

101. Gloaguen, Thibaud, Mark Vero, Robin Staab, and Martin Vechev. “Watch Your Steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning.” arXiv preprint arXiv:2505.16567 (2025).

102. Shuo Wen, Ramon Vinas, Johannes Bues, Camille Lambert, Nadia Grenningloh, Timothee Ferrari, et al. “Generative modeling reveals the connection between cellular morphology and gene expression.” bioRxiv (2026).

103. Johannes Bues, Joern Pezoldt, Camille Lucie Lambert, Benjamin David Hale, Elisa Bugani, Ramon Vinas Torne, Timothee Ferrari, et al. “Single-cell phenomics through integrated imaging and molecular profiling.” bioRxiv (2025)

104. Fabian Gröger, Shuo Wen, Huyen Le, Maria Brbić. “With Limited Data for Multimodal Alignment, Let the STRUCTURE Guide You.” NeurIPS (2025).

105. Choudhury, Monjoy Narayan, Junling Wang, Yifan Hou, and Mrinmaya Sachan. “Can Vision-Language Models Solve Visual Math Equations?” In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 10810–10819 (2025).

106. Filippo Bigi, Paolo Pegolo, Arslan Mazitov and Michele Ceriotti, "Pushing the limits of unconstrained machine-learned interatomic potentials." arXiv preprint arXiv:2601.16195 (2026).

107. Jonas Hübotter, Frederike Lübeck, Lejs Behric, Anton Baumann, Marco Bagatella, Daniel Marta, Ido Hakimi, Idan Shenfeld, Thomas Kleine Buening, Carlos Guestrin, Andreas Krause. “Reinforcement Learning via Self-Distillation”. arXiv preprint arXiv:2601.20802 (2026).