4 citations · 4 across the 4 of their papers we have counts for
4 papers
Structured RAG for Answering Aggregative Questions
Omri Koshorek, Niv Granot, Aviv Alloni +6
Retrieval-Augmented Generation (RAG) has become the dominant approach for answering questions over large corpora. However, current datasets and methods are highly focused on cases…
Diverse Video Generation from a Single Video
Niv Haim, Ben Feinstein, Niv Granot +4
GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single vid…
Diverse Generation from a Single Video Made Possible
Niv Haim, Ben Feinstein, Niv Granot +4
GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single vid…
Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Niv Granot, Ben Feinstein, Assaf Shocher +2
Single image generative models perform synthesis and manipulation tasks by capturing the distribution of patches within a single image. The classical (pre Deep Learning) prevailing…