activity
20182020
most citedIncorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks

21 citations · 21 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Knowledge-Aware Language Model Pretraining

Corby Rosset, Chenyan Xiong, Minh Phan +3

How much knowledge do pretrained language models hold? Recent research observed that pretrained transformers are adept at modeling semantics but it is unclear to what degree they g…

cs.IR2019

Generic Intent Representation in Web Search

Hongfei Zhang, Xia Song, Chenyan Xiong +4

This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a distributed representation space for user intent in search. Leveraging large scale user clicks from Bing sea…

cs.IR201921 cited

Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks

Bhaskar Mitra, Corby Rosset, David Hawking +3

Classical information retrieval (IR) methods, such as query likelihood and BM25, score documents independently w.r.t. each query term, and then accumulate the scores. Assuming quer…

cs.IR2019

An Axiomatic Approach to Regularizing Neural Ranking Models

Corby Rosset, Bhaskar Mitra, Chenyan Xiong +3

Axiomatic information retrieval (IR) seeks a set of principle properties desirable in IR models. These properties when formally expressed provide guidance in the search for better…

cs.IR2018

Optimizing Query Evaluations using Reinforcement Learning for Web Search

Corby Rosset, Damien Jose, Gargi Ghosh +2

In web search, typically a candidate generation step selects a small set of documents---from collections containing as many as billions of web pages---that are subsequently ranked…