PU-DPO applies positive-unlabeled learning to preference optimization so that report generators learn to mention findings that are present but missing from noisy training reports.
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining , pages=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation
PU-DPO applies positive-unlabeled learning to preference optimization so that report generators learn to mention findings that are present but missing from noisy training reports.