A-SHOJAEI/contrastive-qa-verifier-with-adversarial-unanswerable
A dual-encoder system that learns to verify question-answer pair validity through contrastive learning on SQuAD 2.0 and Natural Questions, with adversarial generation of plausible-but-incorrect answers. The model is trained to distinguish between correct answers, near-miss answers (same entity type, wrong entity), and unanswerable questions, enabli
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Python
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MIT
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Last pushed
Feb 21, 2026
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