Výsledky vyhledávání - "Naik, Ankita"

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Retrieval-Based Transformer for Table Augmentation

Autor: Glass, Michael, Wu, Xueqing, Naik, Ankita Rajaram, Rossiello, Gaetano, Gliozzo, Alfio

Data preparation, also called data wrangling, is considered one of the most expensive and time-consuming steps when performing analytics or building machine learning models. Preparing data typically involves collecting and merging data from complex h

Externí odkaz: http://arxiv.org/abs/2306.11843

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Re2G: Retrieve, Rerank, Generate

Autor: Glass, Michael, Rossiello, Gaetano, Chowdhury, Md Faisal Mahbub, Naik, Ankita Rajaram, Cai, Pengshan, Gliozzo, Alfio

As demonstrated by GPT-3 and T5, transformers grow in capability as parameter spaces become larger and larger. However, for tasks that require a large amount of knowledge, non-parametric memory allows models to grow dramatically with a sub-linear inc

Externí odkaz: http://arxiv.org/abs/2207.06300

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Knowledge Base Question Answering by Case-based Reasoning over Subgraphs

Autor: Das, Rajarshi, Godbole, Ameya, Naik, Ankita, Tower, Elliot, Jia, Robin, Zaheer, Manzil, Hajishirzi, Hannaneh, McCallum, Andrew

Question answering (QA) over knowledge bases (KBs) is challenging because of the diverse, essentially unbounded, types of reasoning patterns needed. However, we hypothesize in a large KB, reasoning patterns required to answer a query type reoccur for

Externí odkaz: http://arxiv.org/abs/2202.10610

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Shallow-UWnet : Compressed Model for Underwater Image Enhancement

Autor: Naik, Ankita, Swarnakar, Apurva, Mittal, Kartik

Over the past few decades, underwater image enhancement has attracted increasing amount of research effort due to its significance in underwater robotics and ocean engineering. Research has evolved from implementing physics-based solutions to using v

Externí odkaz: http://arxiv.org/abs/2101.02073

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