71 citations · 415 across the 48 of their papers we have counts for
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cs.CL2020
Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents
Gregory Yauney, Jack Hessel, David Mimno
Images can give us insights into the contextual meanings of words, but current image-text grounding approaches require detailed annotations. Such granular annotation is rare, expen…
cs.CL2020★ 2 cited
Does my multimodal model learn cross-modal interactions? It's harder to tell than you might think!
Jack Hessel, Lillian Lee
Modeling expressive cross-modal interactions seems crucial in multimodal tasks, such as visual question answering. However, sometimes high-performing black-box algorithms turn out…
cs.CL2020
Beyond Instructional Videos: Probing for More Diverse Visual-Textual Grounding on YouTube
Jack Hessel, Zhenhai Zhu, Bo Pang +1
Pretraining from unlabelled web videos has quickly become the de-facto means of achieving high performance on many video understanding tasks. Features are learned via prediction of…