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Found 4 papers, 2 papers with code
Hypothesis Generation with Large Language Models
We focus on hypothesis generation based on data (i. e., labeled examples).
FLamE: Few-shot Learning from Natural Language Explanations
Natural language explanations have the potential to provide rich information that in principle guides model reasoning.
Learning to Ignore Adversarial Attacks
Despite the strong performance of current NLP models, they can be brittle against adversarial attacks.
Investigating the Effect of Natural Language Explanations on Out-of-Distribution Generalization in Few-shot NLI
Although neural models have shown strong performance in datasets such as SNLI, they lack the ability to generalize out-of-distribution (OOD).
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