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20172023
most citedCEDR: Contextualized Embeddings for Document Ranking

241 citations · 686 across the 25 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CL2019

STANCY: Stance Classification Based on Consistency Cues

Kashyap Popat, Subhabrata Mukherjee, Andrew Yates +1

Controversial claims are abundant in online media and discussion forums. A better understanding of such claims requires analyzing them from different perspectives. Stance classific…

cs.CL2019★ 1 cited

Listening between the Lines: Learning Personal Attributes from Conversations

Anna Tigunova, Andrew Yates, Paramita Mirza +1

Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation. In this work we address the acquisition o…

cs.IR2019★ 1 cited

Investigating Retrieval Method Selection with Axiomatic Features

Siddhant Arora, Andrew Yates

We consider algorithm selection in the context of ad-hoc information retrieval. Given a query and a pair of retrieval methods, we propose a meta-learner that predicts how to combin…

cs.CL2019★ 1 cited

Using Multi-Sense Vector Embeddings for Reverse Dictionaries

Michael A. Hedderich, Andrew Yates, Dietrich Klakow +1

Popular word embedding methods such as word2vec and GloVe assign a single vector representation to each word, even if a word has multiple distinct meanings. Multi-sense embeddings…

cs.IR2019★ 241 cited

CEDR: Contextualized Embeddings for Document Ranking

Sean MacAvaney, Andrew Yates, Arman Cohan +1

Although considerable attention has been given to neural ranking architectures recently, far less attention has been paid to the term representations that are used as input to thes…