52 citations · 146 across the 24 of their papers we have counts for
11 papers · 1 filter
Text Counterfactuals via Latent Optimization and Shapley-Guided Search
Quintin Pope, Xiaoli Z. Fern
We study the problem of generating counterfactual text for a classifier as a means for understanding and debugging classification. Given a textual input and a classification model,…
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…
Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference
Reza Ghaeini, Xiaoli Z. Fern, Prasad Tadepalli
Deep learning models have achieved remarkable success in natural language inference (NLI) tasks. While these models are widely explored, they are hard to interpret and it is often…
Joint Neural Entity Disambiguation with Output Space Search
Hamed Shahbazi, Xiaoli Z. Fern, Reza Ghaeini +3
In this paper, we present a novel model for entity disambiguation that combines both local contextual information and global evidences through Limited Discrepancy Search (LDS). Giv…
Dependent Gated Reading for Cloze-Style Question Answering
Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi +1
We present a novel deep learning architecture to address the cloze-style question answering task. Existing approaches employ reading mechanisms that do not fully exploit the interd…
Event Nugget Detection with Forward-Backward Recurrent Neural Networks
Reza Ghaeini, Xiaoli Z. Fern, Liang Huang +1
Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But…
DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference
Reza Ghaeini, Sadid A. Hasan, Vivek Datla +7
We present a novel deep learning architecture to address the natural language inference (NLI) task. Existing approaches mostly rely on simple reading mechanisms for independent enc…