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Sotiris Anagnostidis
Sotiris Anagnostidis
PhD student, ETH Zurich
Verified email at inf.ethz.ch
Title
Cited by
Cited by
Year
OpenAssistant Conversations--Democratizing Large Language Model Alignment
A Köpf, Y Kilcher, D von Rütte, S Anagnostidis, ZR Tam, K Stevens, ...
NeurIPS - Datasets and Benchmarks Track (Oral), 2023
1932023
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse
L Noci, S Anagnostidis, L Biggio, A Orvieto, SP Singh, A Lucchi
NeurIPS, 2022
282022
Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes
A Delitzas, M Parelli, N Hars, G Vlassis, S Anagnostidis, G Bachmann, ...
BMVC (Oral), 2023
11*2023
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
S Anagnostidis, D Pavllo, L Biggio, L Noci, A Lucchi, T Hofmann
NeurIPS (Spotlight), 2023
92023
Direct-search for a class of stochastic min-max problems
S Anagnostidis, A Lucchi, Y Diouane
AISTATS, 2021
72021
Scaling MLPs: A Tale of Inductive Bias
G Bachmann, S Anagnostidis, T Hofmann
NeurIPS, 2023
62023
Nonblocking execution in GraphBLAS
A Mastoras, S Anagnostidis, AJN Yzelman
IPDPSW, 2022
62022
Random Teachers are Good Teachers
F Sarnthein, G Bachmann, S Anagnostidis, T Hofmann
ICML, 2023
42023
Design and implementation for nonblocking execution in GraphBLAS: tradeoffs and performance
A Mastoras, S Anagnostidis, AJN Yzelman
ACM TACO, 2022
42022
The curious case of benign memorization
S Anagnostidis, G Bachmann, L Noci, T Hofmann
ICLR, 2022
42022
Transformer Fusion with Optimal Transport
M Imfeld, J Graldi, M Giordano, T Hofmann, S Anagnostidis, SP Singh
ICLR, 2023
22023
Navigating Scaling Laws: Cpmpute Optimality in Adaptive Model Training
S Anagnostidis, G Bachmann, I Schlag, T Hofmann
arXiv preprint arXiv:2311.03233, 2023
1*2023
A Language Model's Guide Through Latent Space
D von Rütte, S Anagnostidis, G Bachmann, T Hofmann
arXiv preprint arXiv:2402.14433, 2024
2024
Towards Meta-Pruning via Optimal Transport
A Theus, O Geimer, F Wicke, T Hofmann, S Anagnostidis, SP Singh
ICLR (Spotlight), 2024
2024
Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization
E Benarous, S Anagnostidis, L Biggio, T Hofmann
NeurIPS (Workshop on Synthetic Data Generation with Generative AI), 2023
2023
Plausibly Deniable Encryption with Large Language Models
D Pavllo, S Anagnostidis
2023
Mastering Spatial Graph Prediction of Road Networks
S Anagnostidis, A Lucchi, T Hofmann
ICCV, 2023
2023
Cosmology from Galaxy Redshift Surveys with PointNet
S Anagnostidis, A Thomsen, T Kacprzak, T Tröster, L Biggio, A Refregier, ...
NeurIPS (Machine Learning and the Physical Sciences), 2022
2022
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