189 citations · 394 across the 29 of their papers we have counts for
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cs.AI2016★ 13 cited
Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge
Quan Liu, Hui Jiang, Zhen-Hua Ling +3
In this paper, we propose commonsense knowledge enhanced embeddings (KEE) for solving the Pronoun Disambiguation Problems (PDP). The PDP task we investigate in this paper is a comp…
cs.CL2016★ 12 cited
Part-of-Speech Relevance Weights for Learning Word Embeddings
Quan Liu, Zhen-Hua Ling, Hui Jiang +1
This paper proposes a model to learn word embeddings with weighted contexts based on part-of-speech (POS) relevance weights. POS is a fundamental element in natural language. Howev…
cs.AI2016★ 78 cited
Probabilistic Reasoning via Deep Learning: Neural Association Models
Quan Liu, Hui Jiang, Andrew Evdokimov +4
In this paper, we propose a new deep learning approach, called neural association model (NAM), for probabilistic reasoning in artificial intelligence. We propose to use neural netw…