Design biases in NLP systems, such as performance differences for differ...
Improving language model generations according to some user-defined qual...
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-...
Image captioning has conventionally relied on reference-based automatic
...
Scripts - standardized event sequences describing typical everyday activ...
Commonsense AI has long been seen as a near impossible goal – until
rece...
Understanding and creating mathematics using natural mathematical langua...
Providing natural language processing systems with commonsense knowledge...
In social settings, much of human behavior is governed by unspoken rules...
Conditional text generation often requires lexical constraints, i.e., wh...
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...
As AI systems become an increasing part of people's everyday lives, it
b...
Recent advances in commonsense reasoning depend on large-scale
human-ann...
Natural language understanding involves reading between the lines with
i...
Large neural models have demonstrated human-level performance on languag...
To apply eyeshadow without a brush, should I use a cotton swab or a
toot...
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) ...
High-Throughput materials discovery involves the rapid synthesis,
measur...
The ability to represent complex high dimensional probability distributi...
Identifying important components or factors in large amounts of noisy da...