no code implementations • 8 Mar 2023 • Dylan Ebert, Chen Sun, Ellie Pavlick
Given the importance of 3D space in formal models of verb semantics, we expect that these 2D images would result in impoverished representations that fail to capture nuanced differences in meaning.
1 code implementation • *SEM (NAACL) 2022 • Jack Merullo, Dylan Ebert, Carsten Eickhoff, Ellie Pavlick
Lexical semantics and cognitive science point to affordances (i. e. the actions that objects support) as critical for understanding and representing nouns and verbs.
no code implementations • NAACL 2022 • Dylan Ebert, Chen Sun, Ellie Pavlick
Distributional models learn representations of words from text, but are criticized for their lack of grounding, or the linking of text to the non-linguistic world.
no code implementations • Joint Conference on Lexical and Computational Semantics 2020 • Dylan Ebert, Ellie Pavlick
We introduce a new dataset for training and evaluating grounded language models.
no code implementations • WS 2019 • Dylan Ebert, Ellie Pavlick
The fields of cognitive science and philosophy have proposed many different theories for how humans represent {``}concepts{''}.
no code implementations • 25 Mar 2017 • Amir Ghaderi, Srujana Gattupalli, Dylan Ebert, Ali Sharifara, Vassilis Athitsos, Fillia Makedon
As a result of these improvements, the accuracy in recognizing cases where subjects touch their toes has gone from 76. 46% in our previous work to 97. 19% in this paper.
no code implementations • 14 Feb 2017 • Ali Sharifara, Mohd Shafry Mohd Rahim, Farhad Navabifar, Dylan Ebert, Amir Ghaderi, Michalis Papakostas
In this study, an enhanced face detection framework is proposed to improve detection rate based on skin color and provide a validation process.