We introduce the task of scientific fact-checking. Given a corpus of scientific articles and a claim about a scientific finding, a fact-checking model must identify abstracts that support or refute the claim. In addition, it must provide rationales for its predictions in the form of evidentiary sentences from the retrieved abstracts. For this task, we introduce SciFact, a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts , and annotated with labels and rationales.
<clarity> We introduce the task of scientific fact-checking. Given a corpus of scientific articles and a claim about a scientific finding, a fact-checking model must identify abstracts that support or refute the claim. In addition, it must provide rationales for its predictions in the form of evidentiary sentences from the retrieved abstracts. For this task, we introduce SciFact, a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts , and annotated with labels and rationales.
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 identify rationales justifying each decision. To study this task, we introduce SciFact, a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts , and annotated with labels and rationales.