declare-lab/CICERO
The purpose of this repository is to introduce new dialogue-level commonsense inference datasets and tasks. We chose dialogues as the data source because dialogues are known to be complex and rich in commonsense.
Introduces two annotated dialogue datasets with complementary difficulty levels: CICERO-v1 with single inferences per context for generative and multiple-choice tasks, and CICERO-v2 with multiple plausible inferences (multiview) to challenge models on reasoning diversity. Provides DIALeCT, a dialogue-level transformer model for contextual commonsense inference generation, available on Hugging Face with interactive demo. Targets NLP researchers working on commonsense reasoning, dialogue understanding, and instruction-following capabilities in language models.
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Python
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MIT
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Last pushed
Mar 14, 2023
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