52 citations · 58 across the 3 of their papers we have counts for
7 papers
I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews
James O'Neill, Polina Rozenshtein, Ryuichi Kiryo +2
Counterfactual statements describe events that did not or cannot take place. We consider the problem of counterfactual detection (CFD) in product reviews. For this purpose, we anno…
An Overview of Neural Network Compression
James O' Neill
Overparameterized networks trained to convergence have shown impressive performance in domains such as computer vision and natural language processing. Pushing state of the art on…
Compressing Deep Neural Networks via Layer Fusion
James O' Neill, Greg Ver Steeg, Aram Galstyan
This paper proposes \textit{layer fusion} - a model compression technique that discovers which weights to combine and then fuses weights of similar fully-connected, convolutional a…
Do not let the history haunt you -- Mitigating Compounding Errors in Conversational Question Answering
Angrosh Mandya, James O'Neill, Danushka Bollegala +1
The Conversational Question Answering (CoQA) task involves answering a sequence of inter-related conversational questions about a contextual paragraph. Although existing approaches…
Transfer Reward Learning for Policy Gradient-Based Text Generation
James O' Neill, Danushka Bollegala
Task-specific scores are often used to optimize for and evaluate the performance of conditional text generation systems. However, such scores are non-differentiable and cannot be u…
Error-Correcting Neural Sequence Prediction
James O' Neill, Danushka Bollegala
We propose a novel neural sequence prediction method based on \textit{error-correcting output codes} that avoids exact softmax normalization and allows for a tradeoff between speed…