Predicting Scholarly Impact with Temporal Preference Alignment
Background. Predicting the future influence of scientific papers remains a longstanding challenge in bibliometrics and information retrieval. Traditional regression and embedding-based methods estimate citation counts from textual features but fail to capture the inherently relational and temporal nature of scholarly i...