3 citations · 6 across the 5 of their papers we have counts for
8 papers
Decoupled Relative Learning Rate Schedules
Jan Ludziejewski, Jan Małaśnicki, Maciej Pióro +8
In this work, we introduce a novel approach for optimizing LLM training by adjusting learning rates across weights of different components in Transformer models. Traditional method…
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
Jan Ludziejewski, Maciej Pióro, Jakub Krajewski +8
Mixture of Experts (MoE) architectures have significantly increased computational efficiency in both research and real-world applications of large-scale machine learning models. Ho…
Faster Semi-streaming Matchings via Alternating Trees
Slobodan Mitrović, Anish Mukherjee, Piotr Sankowski +1
We design a deterministic algorithm for the -approximate maximum matching problem. Our primary result demonstrates that this problem can be solved in semi-stream…
Online Multi-level Aggregation with Delays and Stochastic Arrivals
Mathieu Mari, Michał Pawłowski, Runtian Ren +1
This paper presents a new research direction for online Multi-Level Aggregation (MLA) with delays. In this problem, we are given an edge-weighted rooted tree , and we have to se…
Scaling Laws for Fine-Grained Mixture of Experts
Jakub Krajewski, Jan Ludziejewski, Kamil Adamczewski +9
Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties,…
Modeling Online Paging in Multi-Core Systems
Mathieu Mari, Anish Mukherjee, Runtian Ren +1
Web requests are growing exponentially since the 90s due to the rapid development of the Internet. This process was further accelerated by the introduction of cloud services. It ha…
Contrastive News and Social Media Linking using BERT for Articles and Tweets across Dual Platforms
Jan Piotrowski, Marek Wachnicki, Mateusz Perlik +9
X (formerly Twitter) has evolved into a contemporary agora, offering a platform for individuals to express opinions and viewpoints on current events. The majority of the topics dis…
LLM generated responses to mitigate the impact of hate speech
Jakub Podolak, Szymon Łukasik, Paweł Balawender +4
In this study, we explore the use of Large Language Models (LLMs) to counteract hate speech. We conducted the first real-life A/B test assessing the effectiveness of LLM-generated…