60 citations · 139 across the 8 of their papers we have counts for
8 papers
MLAN: Language-Based Instruction Tuning Preserves and Transfers Knowledge in Multimodal Language Models
Jianhong Tu, Zhuohao Ni, Nicholas Crispino +8
We present a novel visual instruction tuning strategy to improve the zero-shot task generalization of multimodal large language models by building a firm text-only knowledge base.…
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning
Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai +8
Although supervised learning has enabled high performance for image segmentation, it requires a large amount of labeled training data, which can be difficult to obtain in the medic…
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction
Beliz Gunel, Arda Sahiner, Arjun D. Desai +4
Unrolled neural networks have enabled state-of-the-art reconstruction performance and fast inference times for the accelerated magnetic resonance imaging (MRI) reconstruction task.…
Data-Efficient Information Extraction from Form-Like Documents
Beliz Gunel, Navneet Potti, Sandeep Tata +3
Automating information extraction from form-like documents at scale is a pressing need due to its potential impact on automating business workflows across many industries like fina…
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction
Arjun D Desai, Beliz Gunel, Batu M Ozturkler +6
Deep neural networks have enabled improved image quality and fast inference times for various inverse problems, including accelerated magnetic resonance imaging (MRI) reconstructio…
Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
Beliz Gunel, Jingfei Du, Alexis Conneau +1
State-of-the-art natural language understanding classification models follow two-stages: pre-training a large language model on an auxiliary task, and then fine-tuning the model on…
Self-training Improves Pre-training for Natural Language Understanding
Jingfei Du, Edouard Grave, Beliz Gunel +5
Unsupervised pre-training has led to much recent progress in natural language understanding. In this paper, we study self-training as another way to leverage unlabeled data through…
Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization
Beliz Gunel, Chenguang Zhu, Michael Zeng +1
Neural models have become successful at producing abstractive summaries that are human-readable and fluent. However, these models have two critical shortcomings: they often don't r…