When and Where To Submit A Paper
What is the optimal order in which a researcher should submit their papers to journals of differing quality? I analyze a sequential search model without recall where the researcher's expected value from journal submission depends on the history of past submissions. Acceptances immediately terminate the search process and deliver some payoff, while rejections carry information about the paper's quality, affecting the researcher's belief in acceptance probability over future journals. When journal feedback does not change the paper's quality, the researcher's optimal strategy is monotone in their acceptance payoff. Submission costs distort the researcher's effective acceptance payoff, but maintain monotone optimality. If journals give feedback which can affect the paper's quality, such as through \textit{referee reports}, the search order can change drastically depending on the agent's prior belief about their paper's quality. However, I identify a set of \textit{assortative matched} conditions on feedback such that monotone strategies remain optimal whenever the agent's prior is sufficiently optimistic.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Where to Submit? Helping Researchers to Choose the Right Venue
Whenever researchers write a paper, the same question occurs: {``}Where to submit?{''} In this work, we introduce WTS, an open and interpretable NLP system that recommends conferences and journals to researchers based on…
Confident and Wrong: Silent Semantic Failures in Coding Agents
As coding agents move into production workflows, teams need to know not only whether an agent completes a task, but whether its action can be trusted. We show that completion and trustworthiness diverge sharply and syste…
NTT Neural Machine Translation Systems at WAT 2019
In this paper, we describe our systems that were submitted to the translation shared tasks at WAT 2019. This year, we participated in two distinct types of subtasks, a scientific paper subtask and a timely disclosure sub…
Machine TranslationTranslationUR@NLP_A_Team @ GermEval 2021: Ensemble-based Classification of Toxic, Engaging and Fact-Claiming Comments
In this paper, we report on our approach to addressing the GermEval 2021 Shared Task on the Identification of Toxic, Engaging, and Fact-Claiming Comments for the German language. We submitted three runs for each subtask …
An Ensemble Approach for Aggression Identification in English and Hindi Text
This paper describes our system submitted in the shared task at COLING 2018 TRAC-1: Aggression Identification. The objective of this task was to predict online aggression spread through online textual post or comment. Th…
Aggression Identification