15 citations · 24 across the 5 of their papers we have counts for
5 papers
A Complex KBQA System using Multiple Reasoning Paths
Kechen Qin, Yu Wang, Cheng Li +4
Multi-hop knowledge based question answering (KBQA) is a complex task for natural language understanding. Many KBQA approaches have been proposed in recent years, and most of them…
Ranking-Based Autoencoder for Extreme Multi-label Classification
Bingyu Wang, Li Chen, Wei Sun +3
Extreme Multi-label classification (XML) is an important yet challenging machine learning task, that assigns to each instance its most relevant candidate labels from an extremely l…
Adapting RNN Sequence Prediction Model to Multi-label Set Prediction
Kechen Qin, Cheng Li, Virgil Pavlu +1
We present an adaptation of RNN sequence models to the problem of multi-label classification for text, where the target is a set of labels, not a sequence. Previous such RNN models…
Winning on the Merits: The Joint Effects of Content and Style on Debate Outcomes
Lu Wang, Nick Beauchamp, Sarah Shugars +1
Debate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control. Ideally, however,…
Joint Modeling of Content and Discourse Relations in Dialogues
Kechen Qin, Lu Wang, Joseph Kim
We present a joint modeling approach to identify salient discussion points in spoken meetings as well as to label the discourse relations between speaker turns. A variation of our…