Larisa Markeeva

According to our database, Larisa Markeeva authored at least 18 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

The Illusion of Stochasticity in LLMs.

Xiangming Gu, Soham De, Michalis K. Titsias, Larisa Markeeva, Petar Velickovic, Razvan Pascanu

CoRR, April, 2026

Understanding Performance Gap Between Parallel and Sequential Sampling in Large Reasoning Models.

Xiangming Gu, Soham De, Larisa Markeeva, Petar Velickovic, Razvan Pascanu

CoRR, April, 2026

2025

How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models.

Dharshan Kumaran, Stephen M. Fleming, Larisa Markeeva, Joe Heyward, Andrea Banino, Mrinal Mathur, Razvan Pascanu, Simon Osindero, Benedetto De Martino, Petar Velickovic, Viorica Patraucean

CoRR, July, 2025

2024

Amplifying human performance in combinatorial competitive programming.

Petar Velickovic, Alex Vitvitskyi, Larisa Markeeva, Borja Ibarz, Lars Buesing, Matej Balog, Alexander Novikov

CoRR, 2024

Transformers meet Neural Algorithmic Reasoners.

Wilfried Bounsi, Borja Ibarz, Andrew Dudzik, Jessica B. Hamrick, Larisa Markeeva, Alex Vitvitskyi, Razvan Pascanu, Petar Velickovic

CoRR, 2024

The CLRS-Text Algorithmic Reasoning Language Benchmark.

Larisa Markeeva, Sean McLeish, Borja Ibarz, Wilfried Bounsi, Olga Kozlova, Alex Vitvitskyi, Charles Blundell, Tom Goldstein, Avi Schwarzschild, Petar Velickovic

CoRR, 2024

2023

TT-SDF2PC: Registration of Point Cloud and Compressed SDF Directly in the Memory-Efficient Tensor Train Domain.

Alexey I. Boyko, Anastasiia Kornilova, Rahim Tariverdizadeh, Mirfarid Musavian Ghazani, Larisa Markeeva, Ivan V. Oseledets, Gonzalo Ferrer

CoRR, 2023

Laser: Latent Set Representations for 3D Generative Modeling.

Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosália G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende

CoRR, 2023

Perception Test: A Diagnostic Benchmark for Multimodal Video Models.

Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adrià Recasens, Larisa Markeeva, Dylan Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre Fréchette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, João Carreira

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

TAP-Vid: A Benchmark for Tracking Any Point in a Video.

Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Knowledge distillation: A good teacher is patient and consistent.

Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

QTT-isogeometric solver in two dimensions.

Larisa Markeeva, I. Tsybulin, Ivan V. Oseledets

J. Comput. Phys., 2021

A Generalized Lottery Ticket Hypothesis.

Ibrahim M. Alabdulmohsin, Larisa Markeeva, Daniel Keysers, Ilya O. Tolstikhin

CoRR, 2021

2020

Towards Understanding Normalization in Neural ODEs.

Julia Gusak, Larisa Markeeva, Talgat Daulbaev, Alexandr Katrutsa, Andrzej Cichocki, Ivan V. Oseledets

CoRR, 2020

Interpolated Adjoint Method for Neural ODEs.

Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets

CoRR, 2020

Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs.

Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

One time is not enough: iterative tensor decomposition for neural network compression.

Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Ivan V. Oseledets, Andrzej Cichocki

CoRR, 2019

Automated Multi-Stage Compression of Neural Networks.

Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Philip Blagoveschensky, Andrzej Cichocki, Ivan V. Oseledets

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019