Systems that can automatically define unfamiliar terms hold the promise ...
What would it take to teach a machine to behave ethically? While broad
e...
The common practice for training commonsense models has gone
from-human-...
Despite recent advances in natural language generation, it remains
chall...
Scripts - standardized event sequences describing typical everyday activ...
Natural language inference requires reasoning about contradictions,
nega...
Commonsense AI has long been seen as a near impossible goal – until
rece...
Despite considerable advancements with deep neural language models (LMs)...
Conditional text generation often requires lexical constraints, i.e., wh...
Pretrained Language Models (LMs) generate text with remarkable quality,
...
Natural language rationales could provide intuitive, higher-level
explan...
Recent years have brought about a renewed interest in commonsense
repres...
Abductive and counterfactual reasoning, core abilities of everyday human...
Human understanding of narrative texts requires making commonsense infer...
Recent advances in commonsense reasoning depend on large-scale
human-ann...
Even from a single frame of a still image, people can reason about the
d...
Natural language understanding involves reading between the lines with
i...
Large neural models have demonstrated human-level performance on languag...
Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC a...
Counterfactual reasoning requires predicting how alternative events, con...
Understanding narratives requires reading between the lines, which in tu...
Abductive reasoning is inference to the most plausible explanation. For
...
The Winograd Schema Challenge (WSC), proposed by Levesque et al. (2011) ...
Claims are a fundamental unit of scientific discourse. The exponential g...
We present ATOMIC, an atlas of everyday commonsense reasoning, organized...
Ontology alignment is the task of identifying semantically equivalent
en...
We describe a deployed scalable system for organizing published scientif...
We present a content-based method for recommending citations in an acade...
Pre-trained word embeddings learned from unlabeled text have become a
st...