Anagnostidis, Sotiris

17 publications

CVPR 2025 Autoregressive Distillation of Diffusion Transformers Yeongmin Kim, Sotiris Anagnostidis, Yuming Du, Edgar Schönfeld, Jonas Kohler, Markos Georgopoulos, Albert Pumarola, Ali Thabet, Artsiom Sanakoyeu
CVPR 2025 FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim, Jonas Kohler, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Albert Pumarola, Ali Thabet, Edgar Schönfeld
NeurIPS 2025 Generalized Linear Mode Connectivity for Transformers Alexander Theus, Alessandro Cabodi, Sotiris Anagnostidis, Antonio Orvieto, Sidak Pal Singh, Valentina Boeva
ICLR 2025 Judge Decoding: Faster Speculative Sampling Requires Going Beyond Model Alignment Gregor Bachmann, Sotiris Anagnostidis, Albert Pumarola, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Edgar Schönfeld, Ali Thabet, Jonas K Kohler
ICLRW 2024 A Language Model's Guide Through Latent Space Dimitri von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann
ICML 2024 A Language Model’s Guide Through Latent Space Dimitri Von Rütte, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann
ICML 2024 Navigating Scaling Laws: Compute Optimality in Adaptive Model Training Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag, Thomas Hofmann
ICLR 2024 Towards Meta-Pruning via Optimal Transport Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh
ICLR 2024 Transformer Fusion with Optimal Transport Moritz Imfeld, Jacopo Graldi, Marco Giordano, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh
CVPRW 2023 CLIP-Guided Vision-Language Pre-Training for Question Answering in 3D Scenes Maria Parelli, Alexandros Delitzas, Nikolas Hars, Georgios Vlassis, Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann
NeurIPS 2023 Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann
NeurIPSW 2023 Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization Elior Benarous, Sotiris Anagnostidis, Luca Biggio, Thomas Hofmann
NeurIPS 2023 OpenAssistant Conversations - Democratizing Large Language Model Alignment Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, Shahul Es, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, Alexander Mattick
ICML 2023 Random Teachers Are Good Teachers Felix Sarnthein, Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann
NeurIPS 2023 Scaling MLPs: A Tale of Inductive Bias Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann
ICLR 2023 The Curious Case of Benign Memorization Sotiris Anagnostidis, Gregor Bachmann, Lorenzo Noci, Thomas Hofmann
NeurIPS 2022 Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurelien Lucchi