Abstract：A Deep Multimodal Investigation To Determine the Appropriateness of Scholarly Submissions Present day peer review is a time-consuming process and is still the only gatekeeper of scientific knowledge and wisdomHoweverthe rapid increase in research article submissions these days across different fields is posing significant challenges to the current systemHence the incorporation of Artificial IntelligenceAItechniques to better streamline the existing peer review system is an immediate need in this age of rapid scientific progressAmong manyone particular challenge these days is that the journal editors and conference program chairs are overwhelmed with the ever-increasing rise in article submissionsStudies show that a lot many submissions are not well-informed and do not fit within the scope of the intended journal or conferenceHere in this workwe embark on to investigate how an AI could assist the editors and program chairs in identifying potential out-of-scope submissions based on the past accepted papers of the particular journal or conferenceWe design a multimodal deep neural architecture and investigate the role of every possible channel of information in a research articlefull-textbibliographyimagesto determine its appropriateness to the concerned venueOur approach does not involve any handcrafted featuressolely depends on the past accepting activity of the venueand thereby achieves significant performance on two real-life datasetsOur findings suggest that a system of this kind is possible and with reasonable accuracy could assist the editorschairs in flagging out inappropriate submissionsThe article is mainly concentrated in the submission process of academic journals and conferenceswithout clearly mentioning its application in the libraryThis study mainly discusses how to use deep learning methods to assist editors and chairman of the conference identification that may exceed the categoryA deep neural network architecture is designed in the studywhich is a possible information channelincluding full textreferenceimageimageof each possible information channel of the architecture to determine its appropriateness to specific journals or meetingsThis method does not involve any hand-made characteristicsand only depends on the past acceptance activities to learn