I recommended desk rejections (DR) for 5 out of 14 submissions, as an #ICLR2027 Area Chair. Story behind this: I did not use any LLM detection tools, which are unnecessary and should not be used for judging DR. These submissions shared some shockingly basic problems in scientific writing, and therefore each paper only took me about 10 mins (thank God) to identify and report the issues. 1. Undefined jargon. Writing 101: Your paper must be self-contained. If a term isn't standard knowledge in the field, it should be defined. 2. Not analyzing or pretending to analyze results. Experimental analysis is about providing insights, not simply repeating numbers from figures and tables. Bro, I can read the numbers myself. 3. Missing citations. Scientific claims need support, either from existing literature or in-paper empirical evidence. Fewer than three citations in an entire introduction? Either the work is a once-in-a-century masterpiece, or the claims are hallucinated in the paper. My biggest concern isn't whether these papers were written using LLMs. It's that some submissions fail to meet the most basic standards of scientific communication and therefore should not be reviewed. Considering this has already wasted some reviewers' time, I strongly recommend introducing AI to flag such papers at an earlier stage. Thanks for ICLR's policy on desk rejections. Hope this can save some time for the responsible reviewers.