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07/06/2022
The Role of Complex NLP in Transformers for Text Ranking?
Even though term-based methods such as BM25 provide strong baselines in ...
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04/05/2022
How Different are Pre-trained Transformers for Text Ranking?
In recent years, large pre-trained transformers have led to substantial ...
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10/12/2018
HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents
A high degree of topical diversity is often considered to be an importan...
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06/21/2018
Learning to Rank from Samples of Variable Quality
Training deep neural networks requires many training samples, but in pra...
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11/30/2017
Learning to Learn from Weak Supervision by Full Supervision
In this paper, we propose a method for training neural networks when we ...
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11/15/2017
Words are Malleable: Computing Semantic Shifts in Political and Media Discourse
Recently, researchers started to pay attention to the detection of tempo...
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11/08/2017
Fidelity-Weighted Learning
Training deep neural networks requires many training samples, but in pra...
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11/01/2017
Avoiding Your Teacher's Mistakes: Training Neural Networks with Controlled Weak Supervision
Training deep neural networks requires massive amounts of training data,...
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11/01/2017
On Search Powered Navigation
Query-based searching and browsing-based navigation are the two main com...
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10/03/2017
Finding Talk About the Past in the Discourse of Non-Historians
A heightened interest in the presence of the past has given rise to the ...
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07/24/2017
Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking
Deep neural networks have become a primary tool for solving problems in ...
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04/28/2017
Neural Ranking Models with Weak Supervision
Despite the impressive improvements achieved by unsupervised deep neural...
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09/02/2016
On Horizontal and Vertical Separation in Hierarchical Text Classification
Hierarchy is a common and effective way of organizing data and represent...
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09/06/2015