Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Arakelyan, Erik"'
Modern Question Answering (QA) and Reasoning approaches based on Large Language Models (LLMs) commonly use prompting techniques, such as Chain-of-Thought (CoT), assuming the resulting generation will have a more granular exploration and reasoning ove
Externí odkaz:
http://arxiv.org/abs/2410.11900
Question Answering (QA) datasets have been instrumental in developing and evaluating Large Language Model (LLM) capabilities. However, such datasets are scarce for languages other than English due to the cost and difficulties of collection and manual
Externí odkaz:
http://arxiv.org/abs/2406.14425
Recent studies of the emergent capabilities of transformer-based Natural Language Understanding (NLU) models have indicated that they have an understanding of lexical and compositional semantics. We provide evidence that suggests these claims should
Externí odkaz:
http://arxiv.org/abs/2401.14440
Autor:
Cochez, Michael, Alivanistos, Dimitrios, Arakelyan, Erik, Berrendorf, Max, Daza, Daniel, Galkin, Mikhail, Minervini, Pasquale, Niepert, Mathias, Ren, Hongyu
Knowledge graphs (KGs) are inherently incomplete because of incomplete world knowledge and bias in what is the input to the KG. Additionally, world knowledge constantly expands and evolves, making existing facts deprecated or introducing new ones. Ho
Externí odkaz:
http://arxiv.org/abs/2308.06585
Stance Detection is concerned with identifying the attitudes expressed by an author towards a target of interest. This task spans a variety of domains ranging from social media opinion identification to detecting the stance for a legal claim. However
Externí odkaz:
http://arxiv.org/abs/2306.00765
Answering complex queries on incomplete knowledge graphs is a challenging task where a model needs to answer complex logical queries in the presence of missing knowledge. Prior work in the literature has proposed to address this problem by designing
Externí odkaz:
http://arxiv.org/abs/2301.12313
Neural link predictors are immensely useful for identifying missing edges in large scale Knowledge Graphs. However, it is still not clear how to use these models for answering more complex queries that arise in a number of domains, such as queries us
Externí odkaz:
http://arxiv.org/abs/2011.03459
In the following paper we will consider Navier-Stokes problem and it's interpretation by hyperbolic waves, focusing on wave propagation. We will begin with solution for linear waves, then present problem for non-linear waves. Later we will derive for
Externí odkaz:
http://arxiv.org/abs/1601.05695
Publikováno v:
Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), 5309-5313
STARTPAGE=5309;ENDPAGE=5313;TITLE=Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022)
STARTPAGE=5309;ENDPAGE=5313;TITLE=Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022)
Neural link predictors are useful for identifying missing edges in large scale Knowledge Graphs. However, it is still not clear how to use these models for answering more complex queries containing logical conjunctions (∧), disjunctions (∨), and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::b0d01259dca263439dc2547f17567088
https://research.vu.nl/en/publications/af2bb26b-bbd1-45fc-bd8c-5fd49c41b0d0
https://research.vu.nl/en/publications/af2bb26b-bbd1-45fc-bd8c-5fd49c41b0d0