b'Douwe Kiela'

research

∙ 07/20/2022

DataPerf: Benchmarks for Data-Centric AI Development

Machine learning (ML) research has generally focused on models, while th...

Mark Mazumder, et al. ∙

research

∙ 05/25/2022

Perturbation Augmentation for Fairer NLP

Unwanted and often harmful social biases are becoming ever more salient ...

Rebecca Qian, et al. ∙

research

∙ 04/07/2022

Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality

We present a novel task and dataset for evaluating the ability of vision...

Tristan Thrush, et al. ∙

research

∙ 04/05/2022

Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks

We introduce Dynatask: an open source system for setting up custom NLP t...

Tristan Thrush, et al. ∙

research

∙ 12/16/2021

Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants

In Dynamic Adversarial Data Collection (DADC), human annotators are task...

Max Bartolo, et al. ∙

research

∙ 12/08/2021

FLAVA: A Foundational Language And Vision Alignment Model

State-of-the-art vision and vision-and-language models rely on large-sca...

Amanpreet Singh, et al. ∙

research

∙ 10/16/2021

Analyzing Dynamic Adversarial Training Data in the Limit

To create models that are robust across a wide range of test inputs, tra...

Eric Wallace, et al. ∙

research

∙ 09/08/2021

What's Hidden in a One-layer Randomly Weighted Transformer?

We demonstrate that, hidden within one-layer randomly weighted neural ne...

Sheng Shen, et al. ∙

research

∙ 06/04/2021

Human-Adversarial Visual Question Answering

Performance on the most commonly used Visual Question Answering dataset ...

Sasha Sheng, et al. ∙

research

∙ 06/02/2021

On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study

In adversarial data collection (ADC), a human workforce interacts with a...

Divyansh Kaushik, et al. ∙

research

∙ 05/24/2021

True Few-Shot Learning with Language Models

Pretrained language models (LMs) perform well on many tasks even when le...

Ethan Perez, et al. ∙

research

∙ 04/18/2021

Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation

Despite the availability of very large datasets and pretrained models, s...

Max Bartolo, et al. ∙

research

∙ 04/16/2021

Cross-Modal Retrieval Augmentation for Multi-Modal Classification

Recent advances in using retrieval components over external knowledge so...

Shir Gur, et al. ∙

research

∙ 04/15/2021

Gradient-based Adversarial Attacks against Text Transformers

We propose the first general-purpose gradient-based attack against trans...

Chuan Guo, et al. ∙

research

∙ 04/15/2021

Retrieval Augmentation Reduces Hallucination in Conversation

Despite showing increasingly human-like conversational abilities, state-...

Kurt Shuster, et al. ∙

research

∙ 04/14/2021

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little

A possible explanation for the impressive performance of masked language...

Koustuv Sinha, et al. ∙

research

∙ 03/14/2021

Quasi-Equivalence Discovery for Zero-Shot Emergent Communication

Effective communication is an important skill for enabling information e...

Kalesha Bullard, et al. ∙

research

∙ 03/05/2021

Rissanen Data Analysis: Examining Dataset Characteristics via Description Length

We introduce a method to determine if a certain capability helps to achi...

Ethan Perez, et al. ∙

research

∙ 12/31/2020

Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection

We present a first-of-its-kind large synthetic training dataset for onli...

Bertie Vidgen, et al. ∙

research

∙ 12/30/2020

DynaSent: A Dynamic Benchmark for Sentiment Analysis

We introduce DynaSent ('Dynamic Sentiment'), a new English-language benc...

Christopher Potts, et al. ∙

research

∙ 12/30/2020

Reservoir Transformer

We demonstrate that transformers obtain impressive performance even when...

Sheng Shen, et al. ∙

research

∙ 12/24/2020

I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling

To quantify how well natural language understanding models can capture c...

Yixin Nie, et al. ∙

research

∙ 12/24/2020

To what extent do human explanations of model behavior align with actual model behavior?

Given the increasingly prominent role NLP models (will) play in our live...

Grusha Prasad, et al. ∙

research

∙ 10/29/2020

Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations

Effective communication is an important skill for enabling information e...

Kalesha Bullard, et al. ∙

research

∙ 10/24/2020

ANLIzing the Adversarial Natural Language Inference Dataset

We perform an in-depth error analysis of Adversarial NLI (ANLI), a recen...

Adina Williams, et al. ∙

research

∙ 09/27/2020

Learning Optimal Representations with the Decodable Information Bottleneck

We address the question of characterizing and finding optimal representa...

Yann Dubois, et al. ∙

research

∙ 09/27/2020

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

We propose a simple and efficient multi-hop dense retrieval approach for...

Wenhan Xiong, et al. ∙

research

∙ 05/22/2020

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Large pre-trained language models have been shown to store factual knowl...

Patrick Lewis, et al. ∙

research

∙ 05/10/2020

The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes

This work proposes a new challenge set for multimodal classification, fo...

Douwe Kiela, et al. ∙

research

∙ 05/01/2020

Multi-Dimensional Gender Bias Classification

Machine learning models are trained to find patterns in data. NLP models...

Emily Dinan, et al. ∙

research

∙ 02/22/2020

Unsupervised Question Decomposition for Question Answering

We aim to improve question answering (QA) by decomposing hard questions ...

Ethan Perez, et al. ∙

research

∙ 02/07/2020

I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-oriented dialogue agents

Dialogue research tends to distinguish between chit-chat and goal-orient...

Shrimai Prabhumoye, et al. ∙

research

∙ 02/07/2020

I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-orientated dialogue agents

Dialogue research tends to distinguish between chit-chat and goal-orient...

Shrimai Prabhumoye, et al. ∙

research

∙ 11/20/2019

Generating Interactive Worlds with Text

Procedurally generating cohesive and interesting game environments is ch...

Angela Fan, et al. ∙

research

∙ 11/10/2019

Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation

Models often easily learn biases present in the training data, and their...

Emily Dinan, et al. ∙

research

∙ 10/31/2019

Adversarial NLI: A New Benchmark for Natural Language Understanding

We introduce a new large-scale NLI benchmark dataset, collected via an i...

Yixin Nie, et al. ∙

research

∙ 10/28/2019

Hyperbolic Graph Neural Networks

Learning from graph-structured data is an important task in machine lear...

Qi Liu, et al. ∙

research

∙ 10/03/2019

Generalized Inner Loop Meta-Learning

Many (but not all) approaches self-qualifying as "meta-learning" in deep...

Edward Grefenstette, et al. ∙

research

∙ 09/12/2019

Finding Generalizable Evidence by Learning to Convince Q A Models

We propose a system that finds the strongest supporting evidence for a g...

Ethan Perez, et al. ∙

research

∙ 09/10/2019

Countering Language Drift via Visual Grounding

Emergent multi-agent communication protocols are very different from nat...

Jason Lee, et al. ∙

research

∙ 09/06/2019

Supervised Multimodal Bitransformers for Classifying Images and Text

Self-supervised bidirectional transformer models such as BERT have led t...

Douwe Kiela, et al. ∙

research

∙ 07/22/2019

Why Build an Assistant in Minecraft?

In this document we describe a rationale for a research program aimed at...

Arthur Szlam, et al. ∙

research

∙ 03/07/2019

Learning to Speak and Act in a Fantasy Text Adventure Game

We introduce a large scale crowdsourced text adventure game as a researc...

Jack Urbanek, et al. ∙

research

∙ 02/22/2019

What makes a good conversation? How controllable attributes affect human judgments

A good conversation requires balance -- between simplicity and detail; s...

Abigail See, et al. ∙

research

∙ 02/03/2019

Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings

We consider the task of inferring is-a relationships from large text cor...

Matt Le, et al. ∙

research

∙ 01/31/2019

The Second Conversational Intelligence Challenge (ConvAI2)

We describe the setting and results of the ConvAI2 NeurIPS competition t...

Emily Dinan, et al. ∙

research

∙ 01/29/2019

No Training Required: Exploring Random Encoders for Sentence Classification

We explore various methods for computing sentence representations from p...

John Wieting, et al. ∙

research

∙ 01/25/2019

Emergent Linguistic Phenomena in Multi-Agent Communication Games

In this work, we propose a computational framework in which agents equip...

Laura Graesser, et al. ∙

research

∙ 09/12/2018

Jump to better conclusions: SCAN both left and right

Lake and Baroni (2018) recently introduced the SCAN data set, which cons...

Joost Bastings, et al. ∙

research

∙ 07/09/2018

Talk the Walk: Navigating New York City through Grounded Dialogue

We introduce "Talk The Walk", the first large-scale dialogue dataset gro...

Harm de Vries, et al. ∙

Douwe Kiela

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