3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Labeled Interactive Topic Models
Kyle Seelman, Mozhi Zhang, Jordan Boyd-Graber
Topic models are valuable for understanding extensive document collections, but they don't always identify the most relevant topics. Classical probabilistic and anchor-based topic…
cs.CL2022★ 3 cited
What's Different between Visual Question Answering for Machine "Understanding" Versus for Accessibility?
Yang Trista Cao, Kyle Seelman, Kyungjun Lee +1
In visual question answering (VQA), a machine must answer a question given an associated image. Recently, accessibility researchers have explored whether VQA can be deployed in a r…