Zobrazeno 1 - 10
of 2 353
pro vyhledávání: '"Janicki, P."'
With the growing reliance on digital devices equipped with graphical user interfaces (GUIs), such as computers and smartphones, the need for effective automation tools has become increasingly important. While multimodal large language models (MLLMs)
Externí odkaz:
http://arxiv.org/abs/2410.11872
Autor:
Gibson, Jason B., Janicki, Tesia D., Hire, Ajinkya C., Bishop, Chris, Lane, J. Matthew D., Hennig, Richard G.
Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parameterize the MLIPs remains a significant challenge. This is because MLIPs can fail wh
Externí odkaz:
http://arxiv.org/abs/2409.07610
Autor:
Brzozowski, Mateusz, Janicki, Artur
This article presents a case study demonstrating a non-intrusive method for the well-being monitoring of elderly people. It is based on our real-time energy measurement system, which uses tiny beacons attached to electricity meters. Four participants
Externí odkaz:
http://arxiv.org/abs/2407.00524
In this article, we present the results of experiments with finding an efficient radio transmission method for an electric energy measurement system called OneMeter 2.0. This system offers a way of collecting energy usage data from beacons attached t
Externí odkaz:
http://arxiv.org/abs/2406.18455
Formal disclosure avoidance techniques are necessary to ensure that published data can not be used to identify information about individuals. The addition of statistical noise to unpublished data can be implemented to achieve differential privacy, wh
Externí odkaz:
http://arxiv.org/abs/2406.04448
Simple fine-tuning can embed hidden text into large language models (LLMs), which is revealed only when triggered by a specific query. Applications include LLM fingerprinting, where a unique identifier is embedded to verify licensing compliance, and
Externí odkaz:
http://arxiv.org/abs/2406.02481
Speedable numbers are real numbers which are algorithmically approximable from below and whose approximations can be accelerated nonuniformly. We begin this article by answering a question of Barmpalias by separating a strict subclass that we will re
Externí odkaz:
http://arxiv.org/abs/2404.15811
Spoken Language Understanding (SLU) models are a core component of voice assistants (VA), such as Alexa, Bixby, and Google Assistant. In this paper, we introduce a pipeline designed to extend SLU systems to new languages, utilizing Large Language Mod
Externí odkaz:
http://arxiv.org/abs/2404.02588
Autor:
Hoscilowicz, Jakub, Wiacek, Adam, Chojnacki, Jan, Cieslak, Adam, Michon, Leszek, Urbanevych, Vitalii, Janicki, Artur
In this work, we explore LLM's internal representation space to identify attention heads that contain the most truthful and accurate information. We further developed the Inference Time Intervention (ITI) framework, which lets bias LLM without the ne
Externí odkaz:
http://arxiv.org/abs/2403.18680
Instance segmentation datasets play a crucial role in training accurate and robust computer vision models. However, obtaining accurate mask annotations to produce high-quality segmentation datasets is a costly and labor-intensive process. In this wor
Externí odkaz:
http://arxiv.org/abs/2402.16421