2 citations · 3 across the 8 of their papers we have counts for
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cs.CL2022
Pretraining on Interactions for Learning Grounded Affordance Representations
Jack Merullo, Dylan Ebert, Carsten Eickhoff +1
Lexical semantics and cognitive science point to affordances (i.e. the actions that objects support) as critical for understanding and representing nouns and verbs. However, study…
cs.CL2022
Do Trajectories Encode Verb Meaning?
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. Grounded languag…
cs.CL2020★ 2 cited
A Visuospatial Dataset for Naturalistic Verb Learning
Dylan Ebert, Ellie Pavlick
We introduce a new dataset for training and evaluating grounded language models. Our data is collected within a virtual reality environment and is designed to emulate the quality o…