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Dear All,
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<div>Reviewing is not much fun at the moment, and I assume that nearly any submitted paper uses some kind of AI support ... The difference here, from my perspective, is that the authors have submitted so many papers with similar techniques. They are therefore
speculating that, statistically, some of these papers will be accepted, which is an unfair advantage compared to other authors. I would therefore desk reject for "self-plagiarism".</div>
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<div>Best regards,</div>
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<div>André<br id="lineBreakAtBeginningOfMessage">
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<div>On 15. Jul 2026, at 03:43, Angela Demke Brown via Hotstorage-sc <hotstorage-sc@fsl.cs.sunysb.edu> wrote:</div>
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<div dir="auto">We ran into something similar with SOSP. In our case it was 9 papers from one company/pair of authors and 6 papers from another company and pair of authors, which on investigation appeared to be the same authors using different first names.
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<div dir="auto">Given the lack of policy in the CFP on generative AI use, and the ACM authorship policies, we felt we couldn't do anything other than (a) ask the authors to explain their use of AI and (b) let the papers be rejected on the basis of their quality.
The authors in our case claimed AI use only to polish their writing, which is generally allowed.</div>
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<div dir="auto">I have no solutions to offer to HotStorage, unfortunately. </div>
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<div dir="auto">All the best, </div>
<div dir="auto">Angela </div>
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<div dir="ltr" class="gmail_attr">On Tue, Jul 14, 2026, 7:50 p.m. Ashvin Goel via Hotstorage-sc <<a href="mailto:hotstorage-sc@fsl.cs.sunysb.edu">hotstorage-sc@fsl.cs.sunysb.edu</a>> wrote:<br>
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<div dir="ltr">The 10 papers were submitted by the same set of authors.
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<div>Ashvin</div>
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<div dir="ltr" class="gmail_attr">On Tue, Jul 14, 2026 at 8:28 PM Erez Zadok <<a href="mailto:ezk@fsl.cs.sunysb.edu" target="_blank" rel="noreferrer">ezk@fsl.cs.sunysb.edu</a>> wrote:<br>
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That is a hotly debated topic nowadays among ACM EiCs and multiple conferences. We just had heated debates about this on the ACM ATC SC too. Different people are trying different things to varying degrees of success, from requiring disclosure by authors,
to automated tools, etc. No perfect solutions. ACM seems to have given up on getting an AI-detection tools but are looking into cite-checking tools.<br>
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ACM recently loosened their AI policy: they no longer prohibit it outright but ask authors to disclose AI use if wanted, then ask the reviewers to decide what, if, and how much AI use is ok or not ok. IOW, ACM now shifted the burden onto reviewers. Some are
ok with this change, others less so.<br>
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One problem with any AI detectors is that actual text can easily be flagged as AI-generated even if the authors use AI to spell check, polish the text, or ask AI to shrink the text size: these are considered valid uses of AI that shouldn’t result in rejection.<br>
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That said, the easiest way to catch bad AI use is via citation checks. At TOS, we now validate each citation of a submission before sending it off to be reviewed. Even with search tools, that’s more work but we have no choice: recently we caught several papers
with bad/hallucinated cites deep into the reviewing process (thus wasting reviewers’ precious time). Any paper with obviously bad/hallucinated cites gets desk-rejected, but we also email the authors to see if they can explain themselves first.<br>
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So my suggestions are:<br>
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1. Papers with obviously large portions of AI text should be rejected with minimal reviews. If authors didn’t spend any significant effort to develop the paper, then our reviewers shouldn’t waste their time either. “You get what you paid for” principle.<br>
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2. Papers with too many hallucinated cites should be rejected right away without review. 1-2 cites max may be considered a silly mistake that students sometimes make (I’d ask the authors), but any more should be rejected.<br>
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3. I don’t think we should limit the number of submissions per author. While rare, it’s possible to see 2-3 papers submitted by a subset of the same authors. Now, when you say “a set of authors had submitted 10 papers,” *how many* are in the set?! Is it
the same exact authors who submitted 10 separate papers?<br>
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Thanks,<br>
Erez.<br>
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> On Jul 14, 2026, at 2:18 PM, Ashvin Goel via Hotstorage-sc <<a href="mailto:hotstorage-sc@fsl.cs.sunysb.edu" target="_blank" rel="noreferrer">hotstorage-sc@fsl.cs.sunysb.edu</a>> wrote:<br>
> <br>
> Hi all,<br>
> <br>
> The HS '26 PC chairs (Young-ri and Bryan) are asking for input from us regarding a set of paper submissions that have likely been AI generated. Two reviewers expressed concerns to the chairs. They found several papers with similar concepts applied to different
areas, following a similar structure, language (including hard to understand or strange words) and flaws. The chairs found that a set of authors had submitted 10 papers (13% of the 79 submissions). The reviewers are currently leaning negative on several of
these papers, pointing out that the papers are difficult to understand, describe concepts vaguely, and use unfamiliar language. The positive-leaning papers will be discussed at the PC meeting.<br>
> <br>
> The chairs are looking for input about the best course of action to handle this case of suspected AI-generated papers. On the one hand, ACM allows the use of undisclosed AI. Thus, rejections should be grounded on the paper's technical contribution and novelty,
rather than AI use, which is hard to detect accurately using current AI detection tools. On the other hand, such AI-generated papers will overwhelm reviewers in the future.<br>
> <br>
> Let me know if you have any specific suggestions regarding handling the current case with the 10 submissions. More broadly, we should discuss if HS should put in place any policies for AI generated papers. Here are some examples I have seen:<br>
> <br>
> 1. Using multiple detectors and letting reviewers know so they can decide<br>
> 2. Desk rejecting papers with hallucinated references<br>
> 3. Limiting number of submissions by authors<br>
> <br>
> Thanks<br>
> Ashvin<br>
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