Zobrazeno 1 - 10
of 12 103
pro vyhledávání: '"A. Lakatos"'
Autor:
Lakatos, Mária, Baran, Sándor
In our contemporary era, meteorological weather forecasts increasingly incorporate ensemble predictions of visibility - a parameter of great importance in aviation, maritime navigation, and air quality assessment, with direct implications for public
Externí odkaz:
http://arxiv.org/abs/2406.14159
The use of assistive robots in domestic environments can raise significant ethical concerns, from the risk of individual ethical harm to wider societal ethical impacts including culture flattening and compromise of human dignity. It is therefore esse
Externí odkaz:
http://arxiv.org/abs/2406.09239
Training summarization models requires substantial amounts of training data. However for less resourceful languages like Hungarian, openly available models and datasets are notably scarce. To address this gap our paper introduces HunSum-2 an open-sou
Externí odkaz:
http://arxiv.org/abs/2404.03555
The development of generative large language models (G-LLM) opened up new opportunities for the development of new types of knowledge-based systems similar to ChatGPT, Bing, or Gemini. Fine-tuning (FN) and Retrieval-Augmented Generation (RAG) are the
Externí odkaz:
http://arxiv.org/abs/2403.09727
Autor:
Baran, Sándor, Lakatos, Mária
Publikováno v:
Weather and Forecasting 39 (2024), no 11, 1591-1604
Since the start of the operational use of ensemble prediction systems, ensemble-based probabilistic forecasting has become the most advanced approach in weather prediction. However, despite the persistent development of the last three decades, ensemb
Externí odkaz:
http://arxiv.org/abs/2401.14393
Autor:
Lakatos, Robert, Bogacsovics, Gergo, Harangi, Balazs, Lakatos, Istvan, Tiba, Attila, Toth, Janos, Szabo, Marianna, Hajdu, Andras
The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains.
Externí odkaz:
http://arxiv.org/abs/2306.07786
This workshop focused on identifying the challenges and dynamics between people and robots to foster short interactions and long-lasting relationships in different fields, from educational, service, collaborative, companion, care-home and medical rob
Externí odkaz:
http://arxiv.org/abs/2311.05401
Data augmentation methods for neural machine translation are particularly useful when limited amount of training data is available, which is often the case when dealing with low-resource languages. We introduce a novel augmentation method, which gene
Externí odkaz:
http://arxiv.org/abs/2311.02355
Introduction: Covert tobacco advertisements often raise regulatory measures. This paper presents that artificial intelligence, particularly deep learning, has great potential for detecting hidden advertising and allows unbiased, reproducible, and fai
Externí odkaz:
http://arxiv.org/abs/2309.10561
Publikováno v:
Working with Trouble and Failures in Conversation between humans and Robots (WTF) workshop held alongside the 5th International Conference on Conversational User Interfaces (CUI '23), June 19, 2023, Eindhoven, Netherlands
This paper examines some common problems in Human-Robot Interaction (HRI) causing failures and troubles in Chat. A given use case's design decisions start with the suitable robot, the suitable chatting model, identifying common problems that cause fa
Externí odkaz:
http://arxiv.org/abs/2309.03708