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pro vyhledávání: '"Nikishina, Irina P."'
Wiping out the limitations of Large Language Models -- A Taxonomy for Retrieval Augmented Generation
Current research on RAGs is distributed across various disciplines, and since the technology is evolving very quickly, its unit of analysis is mostly on technological innovations, rather than applications in business contexts. Thus, in this research,
Externí odkaz:
http://arxiv.org/abs/2408.02854
Autor:
Moskvoretskii, Viktor, Tupitsa, Nazarii, Biemann, Chris, Horváth, Samuel, Gorbunov, Eduard, Nikishina, Irina
We present a new approach called MeritOpt based on the Personalized Federated Learning algorithm MeritFed that can be applied to Natural Language Tasks with heterogeneous data. We evaluate it on the Low-Resource Machine Translation task, using the da
Externí odkaz:
http://arxiv.org/abs/2406.12564
Autor:
Moskvoretskii, Viktor, Neminova, Ekaterina, Lobanova, Alina, Panchenko, Alexander, Nikishina, Irina
In this paper, we explore the capabilities of LLMs in capturing lexical-semantic knowledge from WordNet on the example of the LLaMA-2-7b model and test it on multiple lexical semantic tasks. As the outcome of our experiments, we present TaxoLLaMA, th
Externí odkaz:
http://arxiv.org/abs/2403.09207
Autor:
Salnikov, Mikhail, Le, Hai, Rajput, Prateek, Nikishina, Irina, Braslavski, Pavel, Malykh, Valentin, Panchenko, Alexander
Recently, it has been shown that the incorporation of structured knowledge into Large Language Models significantly improves the results for a variety of NLP tasks. In this paper, we propose a method for exploring pre-trained Text-to-Text Language Mo
Externí odkaz:
http://arxiv.org/abs/2310.02166
Argumentation analysis is a field of computational linguistics that studies methods for extracting arguments from texts and the relationships between them, as well as building argumentation structure of texts. This paper is a report of the organizers
Externí odkaz:
http://arxiv.org/abs/2206.09249
Autor:
Nikishina, Irina, Tikhomirov, Mikhail, Logacheva, Varvara, Nazarov, Yuriy, Panchenko, Alexander, Loukachevitch, Natalia
Knowledge graphs such as DBpedia, Freebase or Wikidata always contain a taxonomic backbone that allows the arrangement and structuring of various concepts in accordance with the hypo-hypernym ("class-subclass") relationship. With the rapid growth of
Externí odkaz:
http://arxiv.org/abs/2201.08598
Ontologies, taxonomies, and thesauri are used in many NLP tasks. However, most studies are focused on the creation of these lexical resources rather than the maintenance of the existing ones. Thus, we address the problem of taxonomy enrichment. We ex
Externí odkaz:
http://arxiv.org/abs/2011.11536
This paper describes the results of the first shared task on taxonomy enrichment for the Russian language. The participants were asked to extend an existing taxonomy with previously unseen words: for each new word their systems should provide a ranke
Externí odkaz:
http://arxiv.org/abs/2005.11176
Autor:
Nikishina Irina
Publikováno v:
BIO Web of Conferences, Vol 107, p 05015 (2024)
The paper substantiates the development of a simulation model in the design of the Silk Road Museum. A brief description of the current world museums and exhibitions on the territory of the Russian Federation dedicated to its legacy has been made. A
Externí odkaz:
https://doaj.org/article/dfffde3e4daf4c7fb12f71bd5dabd88a
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