James O'Neill | DeepAI

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∙ 07/19/2023

Gradient Sparsification For Masked Fine-Tuning of Transformers

Fine-tuning pretrained self-supervised language models is widely adopted...

0 James O'Neill, et al. ∙

∙ 07/12/2023

Self-Distilled Quantization: Achieving High Compression Rates in Transformer-Based Language Models

We investigate the effects of post-training quantization and quantizatio...

0 James O'Neill, et al. ∙

∙ 04/25/2022

A Survey on Word Meta-Embedding Learning

Meta-embedding (ME) learning is an emerging approach that attempts to le...

0 Danushka Bollegala, et al. ∙

∙ 04/04/2022

Aligned Weight Regularizers for Pruning Pretrained Neural Networks

While various avenues of research have been explored for iterative pruni...

0 James O'Neill, et al. ∙

∙ 09/30/2021

Deep Neural Compression Via Concurrent Pruning and Self-Distillation

Pruning aims to reduce the number of parameters while maintaining perfor...

0 James O'Neill, et al. ∙

∙ 04/14/2021

I Wish I Would Have Loved This One, But I Didn't – A Multilingual Dataset for Counterfactual Detection in Product Reviews

Counterfactual statements describe events that did not or cannot take pl...

0 James O'Neill, et al. ∙

∙ 02/12/2021

Semantically-Conditioned Negative Samples for Efficient Contrastive Learning

Negative sampling is a limiting factor w.r.t. the generalization of metr...

26 James O'Neill, et al. ∙

∙ 01/22/2021

k-Neighbor Based Curriculum Sampling for Sequence Prediction

Multi-step ahead prediction in language models is challenging due to the...

0 James O'Neill, et al. ∙

∙ 07/29/2020

Compressing Deep Neural Networks via Layer Fusion

This paper proposes layer fusion - a model compression technique that di...

18 James O'Neill, et al. ∙

∙ 06/05/2020

An Overview of Neural Network Compression

Overparameterized networks trained to convergence have shown impressive ...

27 James O'Neill, et al. ∙

∙ 05/12/2020

Do not let the history haunt you – Mitigating Compounding Errors in Conversational Question Answering

The Conversational Question Answering (CoQA) task involves answering a s...

0 Angrosh Mandya, et al. ∙

∙ 09/09/2019

Transfer Reward Learning for Policy Gradient-Based Text Generation

Task-specific scores are often used to optimize for and evaluate the per...

6 James O'Neill, et al. ∙

∙ 01/21/2019

Error-Correcting Neural Sequence Prediction

In this paper we propose a novel neural language modelling (NLM) method ...

2 James O'Neill, et al. ∙

∙ 11/02/2018

Analysing Dropout and Compounding Errors in Neural Language Models

This paper carries out an empirical analysis of various dropout techniqu...

4 James O'Neill, et al. ∙

∙ 09/16/2018

Curriculum-Based Neighborhood Sampling For Sequence Prediction

The task of multi-step ahead prediction in language models is challengin...

0 James O'Neill, et al. ∙

∙ 09/16/2018

Semi-Supervised Multi-Task Word Embeddings

Word embeddings have been shown to benefit from ensembling several word ...

0 James O'Neill, et al. ∙

∙ 08/13/2018

Angular-Based Word Meta-Embedding Learning

Ensembling word embeddings to improve distributed word representations h...

2 James O'Neill, et al. ∙

∙ 05/18/2018

Siamese Capsule Networks

Capsule Networks have shown encouraging results on defacto benchmark com...

0 James O'Neill, et al. ∙

∙ 04/23/2018

Dropping Networks for Transfer Learning

In natural language understanding, many challenges require learning rela...

0 James O'Neill, et al. ∙

∙ 10/04/2017

Automatic Taxonomy Generation - A Use-Case in the Legal Domain

A key challenge in the legal domain is the adaptation and representation...

0 Cécile Robin, et al. ∙

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