12 citations · 55 across the 10 of their papers we have counts for
9 papers · 1 filter
RAVEN: Multitask Retrieval Augmented Vision-Language Learning
Varun Nagaraj Rao, Siddharth Choudhary, Aditya Deshpande +2
The scaling of large language models to encode all the world's knowledge in model parameters is unsustainable and has exacerbated resource barriers. Retrieval-Augmented Generation…
A linearized framework and a new benchmark for model selection for fine-tuning
Aditya Deshpande, Alessandro Achille, Avinash Ravichandran +6
Fine-tuning from a collection of models pre-trained on different domains (a "model zoo") is emerging as a technique to improve test accuracy in the low-data regime. However, model…
Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech
Aditya Deshpande, Jyoti Aneja, Liwei Wang +2
Image captioning is an ambiguous problem, with many suitable captions for an image. To address ambiguity, beam search is the de facto method for sampling multiple captions. However…
Convolutional Image Captioning
Jyoti Aneja, Aditya Deshpande, Alexander Schwing
Image captioning is an important but challenging task, applicable to virtual assistants, editing tools, image indexing, and support of the disabled. Its challenges are due to the v…
Authoring image decompositions with generative models
Jason Rock, Theerasit Issaranon, Aditya Deshpande +1
We show how to extend traditional intrinsic image decompositions to incorporate further layers above albedo and shading. It is hard to obtain data to learn a multi-layer decomposit…
Learning Diverse Image Colorization
Aditya Deshpande, Jiajun Lu, Mao-Chuang Yeh +2
Colorization is an ambiguous problem, with multiple viable colorizations for a single grey-level image. However, previous methods only produce the single most probable colorization…