CERA fine-tunes a dense retriever with triplet contrastive learning plus attention alignment to human rationales, claiming better retrieval effectiveness and faithfulness on clinical trial reports than Contriever and standard hard-negative baselines.
and Caliskan, Aylin
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
AI alignment should target objective floors of competence, accuracy, honesty, and lawfulness rather than aggregated human preferences.
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Position: Align AI to Our Aspirations, Not Our Flaws
AI alignment should target objective floors of competence, accuracy, honesty, and lawfulness rather than aggregated human preferences.