Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Analysis of the Penn Korean Universal Dependency Treebank (PKT-UD): Manual Revision to Build Robust Parsing Model in Korean
In this paper, we first open on important issues regarding the Penn Korean Universal Treebank (PKT-UD) and address these issues by revising the entire corpus manually with the aim of producing…
Abductive Commonsense Reasoning
Abductive reasoning is inference to the most plausible explanation. For example, if Jenny finds her house in a mess when she returns from work, and remembers that she left a window open, she can…
Evaluating Machines by their Real-World Language Use
There is a fundamental gap between how humans understand and use language – in openended, real-world situations – and today’s NLP benchmarks for language understanding. To narrow this gap, we…
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks. While existing methods simply concatenate image region…
TuringAdvice: A Generative and Dynamic Evaluation of Language Use
We propose TuringAdvice, a new challenge task and dataset for language understanding models. Given a written situation that a real person is currently facing, a model must generate helpful advice in…
Multi-View Learning for Vision-and-Language Navigation
Learning to navigate in a visual environment following natural language instructions is a challenging task because natural language instructions are highly variable, ambiguous, and under-specified.…
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
The Winograd Schema Challenge (WSC), proposed by Levesque et al. (2011) as an alternative to the Turing Test, was originally designed as a pronoun resolution problem that cannot be solved based on…
PIQA: Reasoning about Physical Commonsense in Natural Language
To apply eyeshadow without a brush, should I use a cotton swab or a toothpick? Questions requiring this kind of physical commonsense pose a challenge to today's natural language understanding…
Commonsense Knowledge Base Completion with Structural and Semantic Context
Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC and ConceptNet) poses unique challenges compared to the much studied conventional knowledge bases (e.g., Freebase). Commonsense…
Defending Against Neural Fake News
Recent progress in natural language generation has raised dual-use concerns. While applications like summarization and translation are positive, the underlying technology also might enable…