Ankita Naik — accepted AI-conference papers

2022

Knowledge Base Question Answering by Case-based Reasoning over Subgraphs

Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi +2

ICML 2022spotlight

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 various entities in their respective subgraph nei…

Cited by 79 Source ↗PDF ↗code ↗Scholar ↗

2022

Re2G: Retrieve, Rerank, Generate

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

NAACL 2022long

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 increase in computational cost and GPU memory require…

Cited by 145 Source ↗PDF ↗code ↗Scholar ↗