Trevor Cohn

Learning Crosslingual Word Embeddings without Bilingual Corpora

2016 · arXiv (Cornell University)

Crosslingual word embeddings represent lexical items from different languages in the same vector space, enabling transfer of NLP tools. However, previous attempts had expensive resource requirements, difficulty incorporating monolingual data or were unable to handle …

Learning Structural Kernels for Natural Language Processing

2015 · White Rose Research Online (University of Leeds, The University of Sheffield, University of York)

Structural kernels are a flexible learning paradigm that has been widely used in Natural Language Processing. However, the problem of model selection in kernel-based methods is usually overlooked. Previous approaches mostly rely on setting default …

Decoding As Dynamic Programming For Recurrent Autoregressive Models

2020 · Monash University Research Portal (Monash University)

Decoding in autoregressive models (ARMs) consists of searching for a high scoring output sequence under the trained model. Standard decoding methods, based on unidirectional greedy algorithm or beam search, are suboptimal due to error propagation …

Balancing out Bias: Achieving Fairness Through Training Reweighting.

2021 · arXiv (Cornell University)

Bias in natural language processing arises primarily from models learning characteristics of the author such as gender and race when modelling tasks such as sentiment and syntactic parsing. This problem manifests as disparities in error …

A Reminder of its Brittleness: Language Reward Shaping May Hinder Learning for Instruction Following Agents

2023 · arXiv (Cornell University)

Teaching agents to follow complex written instructions has been an important yet elusive goal. One technique for enhancing learning efficiency is language reward shaping (LRS). Within a reinforcement learning (RL) framework, LRS involves training a …

Low Resource Dependency Parsing: Cross-lingual Parameter Sharing in a Neural Network Parser

2015

Long Duong, Trevor Cohn, Steven Bird, Paul Cook. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). 2015.

An Attentional Model for Speech Translation Without Transcription

2016

Long Duong, Antonios Anastasopoulos, David Chiang, Steven Bird, Trevor Cohn. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2016.

Cross-Lingual Word Embeddings for Low-Resource Language Modeling

2017

Oliver Adams, Adam Makarucha, Graham Neubig, Steven Bird, Trevor Cohn. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. 2017.

Graph-to-Sequence Learning using Gated Graph Neural Networks

2018

Many NLP applications can be framed as a graph-to-sequence learning problem. Previous work proposing neural architectures on this setting obtained promising results compared to grammar-based approaches but still rely on linearisation heuristics and/or standard recurrent …

Iterative Back-Translation for Neural Machine Translation

2018

We present iterative back-translation, a method for generating increasingly better synthetic parallel data from monolingual data to train neural machine translation systems. Our proposed method is very simple yet effective and highly applicable in practice. …

Learning how to Active Learn: A Deep Reinforcement Learning Approach

2017

Active learning aims to select a small subset of data for annotation such that a classifier learned on the data is highly accurate. This is usually done using heuristic selection methods, however the effectiveness of …