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VariErr NLI: Separating annotation error from human label variation
VariErr NLI: Separating annotation error from human label variation
PulseAugur coverage of VariErr NLI: Separating annotation error from human label variation — every cluster mentioning VariErr NLI: Separating annotation error from human label variation across labs, papers, and developer communities, ranked by signal.
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Formal semantic structure explains minimal human label variation in NLI tasks
A new research paper explores the extent to which formal semantic structure explains human label variation in natural language inference (NLI) tasks. The study analyzed items from the SNLI and MNLI corpora, finding that…
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LLMs improve NLI dataset error detection and model fine-tuning
A new framework called EVADE uses large language models (LLMs) to generate and validate explanations for error detection in natural language inference (NLI) datasets. This approach aims to reduce the cost and effort ass…