Mateusz Topolewski

Bartosz Bieganowski, Daniel Strzelecki, Robert Skiba et al.

In this paper we summarize the results of the Putnam-like benchmark published by Google DeepMind. This dataset consists of 96 original problems in the spirit of the Putnam Competition and 576 solutions of LLMs. We analyse the performance of models on this set of problems to verify their ability to solve problems from mathematical contests.

Jacek Klimek, Jakub Klimek, Witold Kraskiewicz et al.

Various modifications of TRANSFORMER were recently used to solve time-series forecasting problem. We propose Query Selector - an efficient, deterministic algorithm for sparse attention matrix. Experiments show it achieves state-of-the art results on ETT, Helpdesk and BPI'12 datasets.