1 code implementation • 3 Apr 2023 • Suho Lee, Seungwon Seo, Jihyo Kim, Yejin Lee, Sangheum Hwang
These limitations include a lack of principled ways to determine optimal hyperparameters and performance degradation when the unlabeled target data fail to meet certain requirements such as a closed-set and identical label distribution to the source data.
Source-Free Domain Adaptation Unsupervised Domain Adaptation
no code implementations • 22 Dec 2023 • Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
As the development of large-scale Generative AI models evolve beyond text (1D) generation to include image (2D) and video (3D) generation, processing spatial and temporal information presents unique challenges to quality, performance, and efficiency.
no code implementations • 12 Mar 2024 • Saurabh Agarwal, Bilge Acun, Basil Homer, Mostafa Elhoushi, Yejin Lee, Shivaram Venkataraman, Dimitris Papailiopoulos, Carole-Jean Wu
We observe that there is a high amount of redundancy across heads on which tokens they pay attention to.
no code implementations • ACL (dialdoc) 2021 • Boeun Kim, Dohaeng Lee, Sihyung Kim, Yejin Lee, Jin-Xia Huang, Oh-Woog Kwon, Harksoo Kim
In this paper, we propose two models (i. e., a knowledge span prediction model and a response generation model) for the subtask1 and the subtask2.