12 citations · 25 across the 5 of their papers we have counts for
10 papers · 1 filter
On the Sub-Layer Functionalities of Transformer Decoder
Yilin Yang, Longyue Wang, Shuming Shi +3
There have been significant efforts to interpret the encoder of Transformer-based encoder-decoder architectures for neural machine translation (NMT); meanwhile, the decoder remains…
Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation
Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini +2
We present a new local entity disambiguation system. The key to our system is a novel approach for learning entity representations. In our approach we learn an entity aware extensi…
Saliency Learning: Teaching the Model Where to Pay Attention
Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi +1
Deep learning has emerged as a compelling solution to many NLP tasks with remarkable performances. However, due to their opacity, such models are hard to interpret and trust. Recen…
Learning Scripts as Hidden Markov Models
J. Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa +2
Scripts have been proposed to model the stereotypical event sequences found in narratives. They can be applied to make a variety of inferences including filling gaps in the narrati…
Attentional Multi-Reading Sarcasm Detection
Reza Ghaeini, Xiaoli Z. Fern, Prasad Tadepalli
Recognizing sarcasm often requires a deep understanding of multiple sources of information, including the utterance, the conversational context, and real world facts. Most of the c…
Event Detection with Neural Networks: A Rigorous Empirical Evaluation
J. Walker Orr, Prasad Tadepalli, Xiaoli Fern
Detecting events and classifying them into predefined types is an important step in knowledge extraction from natural language texts. While the neural network models have generally…