23.6k citations
- Carnegie Mellon UniversityUS49 papers
- Google (United States)US37 papers
- California Institute of TechnologyUS33 papers
- Amazon (Germany)DE32 papers
- University of Illinois Urbana-ChampaignUS22 papers
- Microsoft (United States)US20 papers
- Stanford UniversityUS20 papers
- The University of Texas at AustinUS20 papers
- University of California, Los AngelesUS20 papers
- University of California, Santa BarbaraUS19 papers
- University of WashingtonUS19 papers
- Georgia Institute of TechnologyUS17 papers
69 papers · 1 filter
Creating New Voices using Normalizing Flows
Piotr Bilinski, Thomas Merritt, Abdelhamid Ezzerg +5
Creating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of…
Amazon Locker Capacity Management
Samyukta Sethuraman, Ankur Bansal, Setareh Mardan +2
Amazon Locker is a self-service delivery or pickup location where customers can pick up packages and drop off returns. A basic first-come-first-served policy for accepting package…
RBPGAN: Recurrent Back-Projection GAN for Video Super Resolution
Marwah Sulaiman, Zahraa Shehabeldin, Israa Fahmy +5
Recently, video super resolution (VSR) has become a very impactful task in the area of Computer Vision due to its various applications. In this paper, we propose Recurrent Back-Pro…
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models
Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang +5
Embedding-based Retrieval Models (ERMs) have emerged as a promising framework for large-scale text retrieval problems due to powerful large language models. Nevertheless, fine-tuni…
On Early Detection of Hallucinations in Factual Question Answering
Ben Snyder, Marius Moisescu, Muhammad Bilal Zafar
While large language models (LLMs) have taken great strides towards helping humans with a plethora of tasks, hallucinations remain a major impediment towards gaining user trust. Th…
DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines
Chenyu Jiang, Zhen Jia, Shuai Zheng +2
Multi-task model training has been adopted to enable a single deep neural network model (often a large language model) to handle multiple tasks (e.g., question answering and text s…