Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Stance detection is an evolving opinion mining research area motivated by the vast increase
in the variety and volume of user-generated content. In this regard, considerable research …

Evaluating the factuality of long-form text generated by large language models (LMs) is non-
trivial because (1) generations often contain a mixture of supported and unsupported pieces …

Generative search engines directly generate responses to user queries, along with in-line
citations. A prerequisite trait of a trustworthy generative search engine is verifiability, ie …

State-of-the-art models in NLP are now predominantly based on deep neural networks that
are opaque in terms of how they come to make predictions. This limitation has increased …

We introduce scientific claim verification, a new task to select abstracts from the research
literature containing evidence that SUPPORTS or REFUTES a given scientific claim, and to …

Standard test sets for supervised learning evaluate in-distribution generalization.
Unfortunately, when a dataset has systematic gaps (eg, annotation artifacts), these …

Despite pre-trained language models have proven useful for learning high-quality semantic
representations, these models are still vulnerable to simple perturbations. Recent works …

We contribute the largest publicly available dataset of naturally occurring factual claims for
the purpose of automatic claim verification. It is collected from 26 fact checking websites in …

This paper studies the (often implicit) human values behind natural language arguments,
such as to have freedom of thought or to be broadminded. Values are commonly accepted …