Note: The following content is based on my understanding as a 3rd-year Ph.D. student.

The below-given points are a representation of how to write good quality papers. [These reviews were based on the fact that even though the reviewers didn’t find any logic gaps the overall ratings were a weak accept/weak reject.]


  • The reviewers should be able to understand the gist of the paper – within 5 mins.


  • If the reviewer decides to skip certain sections because of fatigue or familiarity with the topic, the reviewer should still be able to catch up with the main theme without getting lost in the flow of paper.


  • An initial glance (just a second or so) of a diagram should reveal what the diagram is all about. The reviewer should not be led into reading the caption to understand what the diagram is trying to say.


  • Presentation (be it writing or graph/image/diagram quality) is the essential key to decide whether a paper would be accepted or not. Remember: Pictures speak a thousand words. An image with a low resolution definitely provides the reviewer ample opportunities to justify giving a low score even though the writing might be excellent. For example, in the picture below seems too detailed in the first glance. The author decided to put this picture in Section 2 (pretty close to the start of the paper). Representations such as this immediately cause the reviewers to feel fatigue and give up understanding what this picture is all about. Possible improvisations of this picture would include a title in the image itself denoting that it is the software stack of the 3D Printer.  Positioning the figure to fit into the overall architecture – more specifically, if this picture was represented in the workflow of the 3D Printer, with the interaction of this software stack with the PC and the hardware, then the reviewer would have understood to give less importance to the inner details thereby reducing his fatigue and motivating him to read on further.




  • In graphs especially, do not omit the units along the axes in-order to enhance readability. In no way does it enhance readability/understandability. The reviewers are given an opportunity to presume whatever values they want (0-0.1 or –inf to -inf) thereby providing them with another set of ample opportunities to reject the paper. An example of a wrong graph is shown below. Thought the author tried improving the readability of the graph by omitting off the X and Y axes labels units, it gives ample opportunities to the reviewer to assume any range of values for the axes thereby rejecting the paper on un-comprehensible reasons the authors never thought about.

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