Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Do NLP Models Know Numbers? Probing Numeracy in Embeddings
The ability to understand and work with numbers (numeracy) is critical for many complex reasoning tasks. Currently, most NLP models treat numbers in text in the same way as other tokens---they embed…
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models
Neural NLP models are increasingly accurate but are imperfect and opaque---they break in counterintuitive ways and leave end users puzzled at their behavior. Model interpretation methods ameliorate…
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
In this work, we present a framework to measure and mitigate intrinsic biases with respect to protected variables --such as gender-- in visual recognition tasks. We show that trained models…
Compositional Questions Do Not Necessitate Multi-hop Reasoning
Multi-hop reading comprehension (RC) questions are challenging because they require reading and reasoning over multiple paragraphs. We argue that it can be difficult to construct large multi-hop RC…
COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et al., 2017).…
HellaSwag: Can a Machine Really Finish Your Sentence?
Recent work by Zellers et al. (2018) introduced a new task of commonsense natural language inference: given an event description such as "A woman sits at a piano," a machine must select the most…
The Risk of Racial Bias in Hate Speech Detection
We investigate how annotators’ insensitivity to differences in dialect can lead to racial bias in automatic hate speech detection models, potentially amplifying harm against minority populations. We…
GrapAL: Connecting the Dots in Scientific Literature
We introduce GrapAL (Graph database of Academic Literature), a versatile tool for exploring and investigating a knowledge base of scientific literature, that was semi-automatically constructed using…
Question Answering is a Format; When is it Useful?
Recent years have seen a dramatic expansion of tasks and datasets posed as question answering, from reading comprehension, semantic role labeling, and even machine translation, to image and video…
Robust Navigation with Language Pretraining and Stochastic Sampling
Core to the vision-and-language navigation (VLN) challenge is building robust instruction representations and action decoding schemes, which can generalize well to previously unseen instructions and…