2.4k citations · 7.6k across the 125 of their papers we have counts for
142 papers
Label Budget Allocation in Multi-Task Learning
Ximeng Sun, Kihyuk Sohn, Kate Saenko +2
The cost of labeling data often limits the performance of machine learning systems. In multi-task learning, related tasks provide information to each other and improve overall perf…
Socratis: Are large multimodal models emotionally aware?
Katherine Deng, Arijit Ray, Reuben Tan +3
Existing emotion prediction benchmarks contain coarse emotion labels which do not consider the diversity of emotions that an image and text can elicit in humans due to various reas…
From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition
Maan Qraitem, Kate Saenko, Bryan A. Plummer
Visual recognition models are prone to learning spurious correlations induced by a biased training set where certain conditions (\eg, Indoors) are over-represented in certain c…
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations
Ping Hu, Ximeng Sun, Stan Sclaroff +1
Multi-label image recognition in the low-label regime is a task of great challenge and practical significance. Previous works have focused on learning the alignment between textual…
Multiscale Video Pretraining for Long-Term Activity Forecasting
Reuben Tan, Matthias De Lange, Michael Iuzzolino +4
Long-term activity forecasting is an especially challenging research problem because it requires understanding the temporal relationships between observed actions, as well as the v…
WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset
Andrea Burns, Krishna Srinivasan, Joshua Ainslie +5
Webpages have been a rich resource for language and vision-language tasks. Yet only pieces of webpages are kept: image-caption pairs, long text articles, or raw HTML, never all in…