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08/23/2023
Curriculum Learning with Adam: The Devil Is in the Wrong Details
Curriculum learning (CL) posits that machine learning models – similar t...
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09/30/2022
Emergent Communication: Generalization and Overfitting in Lewis Games
Lewis signaling games are a class of simple communication games for simu...
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05/27/2022
AANG: Automating Auxiliary Learning
When faced with data-starved or highly complex end-tasks, it is commonpl...
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04/13/2022
Distributionally Robust Models with Parametric Likelihood Ratios
As machine learning models are deployed ever more broadly, it becomes in...
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10/12/2021
Balancing Average and Worst-case Accuracy in Multitask Learning
When training and evaluating machine learning models on a large number o...
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09/15/2021
Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative
Pre-training, where models are trained on an auxiliary objective with ab...
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09/03/2021
Learning Neural Models for Natural Language Processing in the Face of Distributional Shift
The dominating NLP paradigm of training a strong neural predictor to per...
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06/14/2021
Examining and Combating Spurious Features under Distribution Shift
A central goal of machine learning is to learn robust representations th...
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03/18/2021
Modeling the Second Player in Distributionally Robust Optimization
Distributionally robust optimization (DRO) provides a framework for trai...
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04/14/2020
Weight Poisoning Attacks on Pre-trained Models
Recently, NLP has seen a surge in the usage of large pre-trained models....
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11/22/2019
Optimizing Data Usage via Differentiable Rewards
To acquire a new skill, humans learn better and faster if a tutor, based...
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06/27/2019
Findings of the First Shared Task on Machine Translation Robustness
We share the findings of the first shared task on improving robustness o...
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05/25/2019
Are Sixteen Heads Really Better than One?
Attention is a powerful and ubiquitous mechanism for allowing neural mod...
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03/19/2019
compare-mt: A Tool for Holistic Comparison of Language Generation Systems
In this paper, we describe compare-mt, a tool for holistic analysis and ...
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03/15/2019
On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models
Adversarial examples --- perturbations to the input of a model that elic...
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09/02/2018
MTNT: A Testbed for Machine Translation of Noisy Text
Noisy or non-standard input text can cause disastrous mistranslations in...
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05/04/2018
Extreme Adaptation for Personalized Neural Machine Translation
Every person speaks or writes their own flavor of their native language,...
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05/31/2017
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology Based Representations
We investigate the pertinence of methods from algebraic topology for tex...
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01/15/2017
DyNet: The Dynamic Neural Network Toolkit
We describe DyNet, a toolkit for implementing neural network models base...
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08/01/2016