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Found 5 papers, 3 papers with code
Sources of Hallucination by Large Language Models on Inference Tasks
Large Language Models (LLMs) are claimed to be capable of Natural Language Inference (NLI), necessary for applied tasks like question answering and summarization.
Smoothing Entailment Graphs with Language Models
The diversity and Zipfian frequency distribution of natural language predicates in corpora leads to sparsity in Entailment Graphs (EGs) built by Open Relation Extraction (ORE).
Modality and Negation in Event Extraction
Language provides speakers with a rich system of modality for expressing thoughts about events, without being committed to their actual occurrence.
Multivalent Entailment Graphs for Question Answering
Drawing inferences between open-domain natural language predicates is a necessity for true language understanding.
Learning Negation Scope from Syntactic Structure
We present a semi-supervised model which learns the semantics of negation purely through analysis of syntactic structure.
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