ITA trains LLMs to generate and score arguments for ternary claim verification and uses argumentation semantics to derive faithful true/false/uncertain predictions from those structures.
FEVER: a large-scale dataset for fact extraction and VERification
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Neurosymbolic Learning for Inference-Time Argumentation
ITA trains LLMs to generate and score arguments for ternary claim verification and uses argumentation semantics to derive faithful true/false/uncertain predictions from those structures.