Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Can, Ozan Arkan"'
Publikováno v:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, pp. 4610-4620
How to best integrate linguistic and perceptual processing in multi-modal tasks that involve language and vision is an important open problem. In this work, we argue that the common practice of using language in a top-down manner, to direct visual at
Externí odkaz:
http://arxiv.org/abs/2003.12739
Autor:
Can, Ozan Arkan, Martires, Pedro Zuidberg Dos, Persson, Andreas, Gaal, Julian, Loutfi, Amy, De Raedt, Luc, Yuret, Deniz, Saffiotti, Alessandro
Human-robot interaction often occurs in the form of instructions given from a human to a robot. For a robot to successfully follow instructions, a common representation of the world and objects in it should be shared between humans and the robot so t
Externí odkaz:
http://arxiv.org/abs/1904.13324
Autor:
Can, Ozan Arkan, Yuret, Deniz
In this paper, we present a state-of-the-art model and introduce a new dataset for grounded language learning. Our goal is to develop a model that can learn to follow new instructions given prior instruction-perception-action examples. We based our w
Externí odkaz:
http://arxiv.org/abs/1805.07952
Publikováno v:
SemEval@NAACL-HLT
Proceedings of the 13th Workshop on Semantic Evaluation
Proceedings of the 13th Workshop on Semantic Evaluation
This paper describes our system for SemEval-2019 Task 4: Hyperpartisan News Detection (Kiesel et al., 2019). We use pretrained BERT (Devlin et al., 2018) architecture and investigate the effect of different fine tuning regimes on the final classifica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9da0dc2850f6f65cfbfee7752ed59bb1
https://doi.org/10.18653/v1/s19-2175
https://doi.org/10.18653/v1/s19-2175
