activity
20172022
most citedScaling Instruction-Finetuned Language Models

1.2k citations · 1.9k across the 28 of their papers we have counts for

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Showing cs.IRShow all

12 papers · 1 filter

cs.IR2021

Rethinking Search: Making Domain Experts out of Dilettantes

Donald Metzler, Yi Tay, Dara Bahri +1

When experiencing an information need, users want to engage with a domain expert, but often turn to an information retrieval system, such as a search engine, instead. Classical inf…

cs.IR2020

Surprise: Result List Truncation via Extreme Value Theory

Dara Bahri, Che Zheng, Yi Tay +2

Work in information retrieval has largely been centered around ranking and relevance: given a query, return some number of results ordered by relevance to the user. The problem of…

cs.IR2020

Choppy: Cut Transformer For Ranked List Truncation

Dara Bahri, Yi Tay, Che Zheng +2

Work in information retrieval has traditionally focused on ranking and relevance: given a query, return some number of results ordered by relevance to the user. However, the proble…

cs.IR20192 cited

Quaternion Collaborative Filtering for Recommendation

Shuai Zhang, Lina Yao, Lucas Vinh Tran +2

This paper proposes Quaternion Collaborative Filtering (QCF), a novel representation learning method for recommendation. Our proposed QCF relies on and exploits computation with Qu…

cs.IR20197 cited

DeepRec: An Open-source Toolkit for Deep Learning based Recommendation

Shuai Zhang, Yi Tay, Lina Yao +2

Deep learning based recommender systems have been extensively explored in recent years. However, the large number of models proposed each year poses a big challenge for both resear…

cs.IR2018

HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems

Lucas Vinh Tran, Yi Tay, Shuai Zhang +2

This paper investigates the notion of learning user and item representations in non-Euclidean space. Specifically, we study the connection between metric learning in hyperbolic spa…