1 code implementation • 20 Nov 2023 • Shachar Rosenman, Vasudev Lal, Phillip Howard
In this work, we present NeuroPrompts, an adaptive framework that automatically enhances a user's prompt to improve the quality of generations produced by text-to-image models.
1 code implementation • 31 May 2023 • Xiao Xu, Bei Li, Chenfei Wu, Shao-Yen Tseng, Anahita Bhiwandiwalla, Shachar Rosenman, Vasudev Lal, Wanxiang Che, Nan Duan
With only 4M VLP data, ManagerTower achieves superior performances on various downstream VL tasks, especially 79. 15% accuracy on VQAv2 Test-Std, 86. 56% IR@1 and 95. 64% TR@1 on Flickr30K.
no code implementations • 24 Aug 2022 • Avinash Madasu, Estelle Aflalo, Gabriela Ben Melech Stan, Shachar Rosenman, Shao-Yen Tseng, Gedas Bertasius, Vasudev Lal
In this paper, we propose a framework MuMUR, that utilizes knowledge transfer from a multilingual model to boost the performance of multi-modal (image and video) retrieval.
1 code implementation • 17 Jun 2022 • Xiao Xu, Chenfei Wu, Shachar Rosenman, Vasudev Lal, Wanxiang Che, Nan Duan
Vision-Language (VL) models with the Two-Tower architecture have dominated visual-language representation learning in recent years.
no code implementations • 9 Oct 2020 • Amir DN Cohen, Shachar Rosenman, Yoav Goldberg
The current supervised relation classification (RC) task uses a single embedding to represent the relation between a pair of entities.
Ranked #1 on Relation Extraction on SemEval-2010 Task-8
1 code implementation • EMNLP 2020 • Shachar Rosenman, Alon Jacovi, Yoav Goldberg
The process of collecting and annotating training data may introduce distribution artifacts which may limit the ability of models to learn correct generalization behavior.