Direct-Search for a Class of Stochastic Min-Max Problems. - Sotirios-Konstantinos Anagnostidis; Aurélien Lucchi; Youssef Diouane (AISTATS, 2021)

Nonblocking execution in GraphBLAS. - Aristeidis Mastoras; Sotiris Anagnostidis; Albert-Jan Nicholas Yzelman (IPDPS Workshops, 2022)

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. - Lorenzo Noci; Sotiris Anagnostidis; Luca Biggio; Antonio Orvieto; Sidak Pal Singh; Aurélien Lucchi (NeurIPS, 2022)

Cosmology from Galaxy Redshift Surveys with PointNet. - Sotiris Anagnostidis; Arne Thomsen; Tomasz Kacprzak; Tilman Tröster; Luca Biggio; Alexandre Refregier; Thomas Hofmann 001 (CoRR, 2022)

Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes. - Alexandros Delitzas; Maria Parelli; Nikolas Hars; Georgios Vlassis; Sotirios-Konstantinos Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (BMVC, 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 001 (CVPR Workshops, 2023)

Mastering Spatial Graph Prediction of Road Networks. - Sotiris Anagnostidis; Aurélien Lucchi; Thomas Hofmann 001 (ICCV, 2023)

The Curious Case of Benign Memorization. - Sotiris Anagnostidis; Gregor Bachmann; Lorenzo Noci; Thomas Hofmann 001 (ICLR, 2023)

Random Teachers are Good Teachers. - Felix Sarnthein; Gregor Bachmann; Sotiris Anagnostidis; Thomas Hofmann 001 (ICML, 2023)

Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. - Sotiris Anagnostidis; Dario Pavllo; Luca Biggio; Lorenzo Noci; Aurélien Lucchi; Thomas Hofmann 001 (NeurIPS, 2023)

Scaling MLPs: A Tale of Inductive Bias. - Gregor Bachmann; Sotiris Anagnostidis; Thomas Hofmann 001 (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; et al. (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; Nguyen Minh Duc; Oliver Stanley; Richárd Nagyfi; Shahul ES; Sameer Suri; et al. (CoRR, 2023)

Navigating Scaling Laws: Accelerating Vision Transformer's Training via Adaptive Strategies. - Sotiris Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (CoRR, 2023)

Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization. - Elior Benarous; Sotiris Anagnostidis; Luca Biggio; Thomas Hofmann 001 (CoRR, 2023)

Design and Implementation for Nonblocking Execution in GraphBLAS: Tradeoffs and Performance. - Aristeidis Mastoras; Sotiris Anagnostidis; Albert-Jan Nicholas Yzelman (ACM Trans. Archit. Code Optim., 2023)

Transformer Fusion with Optimal Transport. - Moritz Imfeld; Jacopo Graldi; Marco Giordano; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Towards Meta-Pruning via Optimal Transport. - Alexander Theus; Olin Geimer; Friedrich Wicke; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (ICLR, 2024)

Navigating Scaling Laws: Compute Optimality in Adaptive Model Training. - Sotiris Anagnostidis; Gregor Bachmann; Imanol Schlag; Thomas Hofmann 001 (ICML, 2024)

A Language Model's Guide Through Latent Space. - Dimitri von Rütte; Sotiris Anagnostidis; Gregor Bachmann; Thomas Hofmann 001 (ICML, 2024)

How Susceptible are LLMs to Influence in Prompts? - Sotiris Anagnostidis; Jannis Bulian (CoRR, 2024)

MegaPortrait: Revisiting Diffusion Control for High-fidelity Portrait Generation. - Han Yang; Sotiris Anagnostidis; Enis Simsar; Thomas Hofmann 001 (CoRR, 2024)

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 K. Thabet; Edgar Schönfeld (CVPR, 2025)

Autoregressive Distillation of Diffusion Transformers. - Yeongmin Kim; Sotiris Anagnostidis; Yuming Du; Edgar Schönfeld; Jonas Kohler; Markos Georgopoulos; Albert Pumarola; Ali K. Thabet; Artsiom Sanakoyeu (CVPR, 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 K. Thabet; Jonas Kohler (ICLR, 2025)

IC-Portrait: In-Context Matching for View-Consistent Personalized Portrait. - Han Yang; Enis Simsar; Sotiris Anagnostidis; Yanlong Zang; Thomas Hofmann 001; Ziwei Liu (CoRR, 2025)

Exploring Magnitude Preservation and Rotation Modulation in Diffusion Transformers. - Eric Tillman Bill; Cristian Perez Jensen; Sotiris Anagnostidis; Dimitri von Rütte (CoRR, 2025)

Generalized Linear Mode Connectivity for Transformers. - Alexander Theus; Alessandro Cabodi; Sotiris Anagnostidis; Antonio Orvieto; Sidak Pal Singh; Valentina Boeva (CoRR, 2025)

Model Fusion via Neuron Interpolation. - Phoomraphee Luenam; Andreas Spanopoulos; Amit Sant; Thomas Hofmann 001; Sotiris Anagnostidis; Sidak Pal Singh (CoRR, 2025)