1 citations · 1 across the 2 of their papers we have counts for
4 papers
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning
Shuo Xie, Jiahao Qiu, Ankita Pasad +3
While transferring a pretrained language model, common approaches conventionally attach their task-specific classifiers to the top layer and adapt all the pretrained layers. We inv…
Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos
Ankita Pasad, Ariel Gordon, Tsung-Yi Lin +1
We leverage unsupervised learning of depth, egomotion, and camera intrinsics to improve the performance of single-image semantic segmentation, by enforcing 3D-geometric and tempora…
Taskology: Utilizing Task Relations at Scale
Yao Lu, Sören Pirk, Jan Dlabal +6
Many computer vision tasks address the problem of scene understanding and are naturally interrelated e.g. object classification, detection, scene segmentation, depth estimation, et…
On the Contributions of Visual and Textual Supervision in Low-Resource Semantic Speech Retrieval
Ankita Pasad, Bowen Shi, Herman Kamper +1
Recent work has shown that speech paired with images can be used to learn semantically meaningful speech representations even without any textual supervision. In real-world low-res…