198 citations · 949 across the 29 of their papers we have counts for
4 papers · 1 filter
SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval
Liang Pang, Jun Xu, Qingyao Ai +3
In learning-to-rank for information retrieval, a ranking model is automatically learned from the data and then utilized to rank the sets of retrieved documents. Therefore, an ideal…
ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
Hainan Zhang, Yanyan Lan, Liang Pang +2
In multi-turn dialogue generation, response is usually related with only a few contexts. Therefore, an ideal model should be able to detect these relevant contexts and produce a su…
A Deep Look into Neural Ranking Models for Information Retrieval
Jiafeng Guo, Yixing Fan, Liang Pang +6
Ranking models lie at the heart of research on information retrieval (IR). During the past decades, different techniques have been proposed for constructing ranking models, from tr…
HAS-QA: Hierarchical Answer Spans Model for Open-domain Question Answering
Liang Pang, Yanyan Lan, Jiafeng Guo +3
This paper is concerned with open-domain question answering (i.e., OpenQA). Recently, some works have viewed this problem as a reading comprehension (RC) task, and directly applied…