113 citations · 1.1k across the 69 of their papers we have counts for
8 papers · 2 filters
Neuron Interaction Based Representation Composition for Neural Machine Translation
Jian Li, Xing Wang, Baosong Yang +3
Recent NLP studies reveal that substantial linguistic information can be attributed to single neurons, i.e., individual dimensions of the representation vectors. We hypothesize tha…
Improving Question Generation With to the Point Context
Jingjing Li, Yifan Gao, Lidong Bing +2
Question generation (QG) is the task of generating a question from a reference sentence and a specified answer within the sentence. A major challenge in QG is to identify answer-re…
Improving Word Representations: A Sub-sampled Unigram Distribution for Negative Sampling
Wenxiang Jiao, Irwin King, Michael R. Lyu
Word2Vec is the most popular model for word representation and has been widely investigated in literature. However, its noise distribution for negative sampling is decided by empir…
PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition
Wenxiang Jiao, Michael R. Lyu, Irwin King
Utterance-level emotion recognition (ULER) is a significant research topic for understanding human behaviors and developing empathetic chatting machines in the artificial intellige…
Towards Understanding Neural Machine Translation with Word Importance
Shilin He, Zhaopeng Tu, Xing Wang +3
Although neural machine translation (NMT) has advanced the state-of-the-art on various language pairs, the interpretability of NMT remains unsatisfactory. In this work, we propose…
HiGRU: Hierarchical Gated Recurrent Units for Utterance-level Emotion Recognition
Wenxiang Jiao, Haiqin Yang, Irwin King +1
In this paper, we address three challenges in utterance-level emotion recognition in dialogue systems: (1) the same word can deliver different emotions in different contexts; (2) s…