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of 47
pro vyhledávání: '"I.7.m"'
The world is evolving and so is the vocabulary used to discuss topics in speech. Analysing political speech data from more than 30 years requires the use of flexible topic models to uncover the latent topics and their change in prevalence over time a
Externí odkaz:
http://arxiv.org/abs/2410.18486
Keyphrase selection is a challenging task in natural language processing that has a wide range of applications. Adapting existing supervised and unsupervised solutions for the Russian language faces several limitations due to the rich morphology of R
Externí odkaz:
http://arxiv.org/abs/2410.18040
Autor:
Glazkova, Anna, Morozov, Dmitry
Keyphrase selection plays a pivotal role within the domain of scholarly texts, facilitating efficient information retrieval, summarization, and indexing. In this work, we explored how to apply fine-tuned generative transformer-based models to the spe
Externí odkaz:
http://arxiv.org/abs/2409.10640
Text clustering is an important method for organising the increasing volume of digital content, aiding in the structuring and discovery of hidden patterns in uncategorised data. The effectiveness of text clustering largely depends on the selection of
Externí odkaz:
http://arxiv.org/abs/2403.15112
The ability of zero-shot translation emerges when we train a multilingual model with certain translation directions; the model can then directly translate in unseen directions. Alternatively, zero-shot translation can be accomplished by pivoting thro
Externí odkaz:
http://arxiv.org/abs/2403.00144
Autor:
Glazkova, Anna, Morozov, Dmitry
Publikováno v:
Communications in Computer and Information Science, vol 2086, pp. 249--265
Modern models for text generation show state-of-the-art results in many natural language processing tasks. In this work, we explore the effectiveness of abstractive text summarization models for keyphrase selection. A list of keyphrases is an importa
Externí odkaz:
http://arxiv.org/abs/2312.10700
Autor:
Glazkova, Anna
The paper describes a system developed for Task 1 at SMM4H 2023. The goal of the task is to automatically distinguish tweets that self-report a COVID-19 diagnosis (for example, a positive test, clinical diagnosis, or hospitalization) from those that
Externí odkaz:
http://arxiv.org/abs/2311.00732
While paper instructions are one of the mainstream medium for sharing knowledge, consuming such instructions and translating them into activities are inefficient due to the lack of connectivity with physical environment. We present PaperToPlace, a no
Externí odkaz:
http://arxiv.org/abs/2308.13924
Knowledge distillation (KD) is the process of transferring knowledge from a large model to a small one. It has gained increasing attention in the natural language processing community, driven by the demands of compressing ever-growing language models
Externí odkaz:
http://arxiv.org/abs/2307.15190
Currently, dialogue systems have achieved high performance in processing text-based communication. However, they have not yet effectively incorporated visual information, which poses a significant challenge. Furthermore, existing models that incorpor
Externí odkaz:
http://arxiv.org/abs/2305.10512