Using ICLR 2022/2023 reviewer novelty scores as labels, the study reports that the introduction, results, and discussion sections form the most effective input combination for automated novelty prediction.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
SC4ANM: Identifying Optimal Section Combinations for Automated Novelty Prediction in Academic Papers
Using ICLR 2022/2023 reviewer novelty scores as labels, the study reports that the introduction, results, and discussion sections form the most effective input combination for automated novelty prediction.