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20172023
most citedCBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases

8 citations · 11 across the 3 of their papers we have counts for

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cs.CL2023

Machine Reading Comprehension using Case-based Reasoning

Dung Thai, Dhruv Agarwal, Mudit Chaudhary +6

We present an accurate and interpretable method for answer extraction in machine reading comprehension that is reminiscent of case-based reasoning (CBR) from classical AI. Our meth…

cs.CL20228 cited

CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases

Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz +7

Knowledge bases (KBs) are often incomplete and constantly changing in practice. Yet, in many question answering applications coupled with knowledge bases, the sparse nature of KBs…

cs.CL2021

TABBIE: Pretrained Representations of Tabular Data

Hiroshi Iida, Dung Thai, Varun Manjunatha +1

Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as…

cs.CL2021

Case-based Reasoning for Natural Language Queries over Knowledge Bases

Rajarshi Das, Manzil Zaheer, Dung Thai +6

It is often challenging to solve a complex problem from scratch, but much easier if we can access other similar problems with their solutions -- a paradigm known as case-based reas…

cs.CL2017

Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling

Dung Thai, Shikhar Murty, Trapit Bansal +3

In textual information extraction and other sequence labeling tasks it is now common to use recurrent neural networks (such as LSTM) to form rich embedded representations of long-t…