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Text of the page (random words):
use writing plugins that improve their writing but also trigger the tool the algorithms for such tools also may change and are usually only free for a small amount of text or will hide the results behind a paywall modal however such tools have improved over time and the best ones usually non free have 95 accuracy rates 4 and they can help check dozens of suspected edits for further inspection a consistently high ai score could warrant additional investigation mixed scores are lower signal since other editors may have changed the content substantially and wiki formatting markup can throw some tools off useful tools edit user sohom datta link dispenser a tool that checks an article s external links for 404 errors indicating they may have been hallucinated it is worth doing a site search for the article subject to make sure bibtest a tool that checks whether an article s isbns exist edit filter logs you can search for the user in edit filter logs to see if they triggered any ones relevant to llm use ones to look for include 893 1030 1325 1346 1369 see for them all together gptzero for wikipedia not that reliable but consistently high ai scores or a 100 ai score is worth something pangram one of the most reliable automated detectors despite high false negatives but it is better used as a sanity check and shouldn t be a substitute for personal judgement engaging with editors suspected of llm use edit many editors who use llms do so in good faith and are often unaware of wp nollm user lwg these are the llm users in your neighborhood discusses the different types of editors you may encounter they are often newcomers who are overwhelmed by the steep learning curve for editing or people using llms to compensate for a low proficiency in english it s therefore paramount to be wary of wp bite when encountering llm generated content it s worth warning the author whether with uw ai or a hand written message again wikiblame is useful for finding the author if it isn t clear from the page history if you re unable to manage the cleanup of the user s edits yourself consider making a report at the ai noticeboard unlike at wp ani there s no requirement to notify an editor of a report about them warnings may sometimes be better framed as questions about whether they ve used llms especially if there s some uncertainty as they re less combative more collegial and may solicit some useful information that will help with cleanup for good faith newcomers it is important to be patient and empathetic when explaining things to point them towards guidance and possibly mentorship and to obtain a commitment to not use llms in future whether on their talk page or at the ai noticeboard though often newcomers will stop editing due to this being a very negative early experience you can also kindly ask them to help cleanup their previous edits for non native english speakers who have used llms the same applies but in addition it s worth communicating that content doesn t need to be written in perfect english wp imperfect questioning someone s proficiency in english can be a sensitive topic you may want to speak generally and point them to a wikipedia in their native language if they don t already edit there meta list of wikipedias for editors whose proficiency in english is too low to contribute constructively there is little you can do other than communicate clearly that they shouldn t edit wikis whose languages they don t speak this ll usually become obvious because they continue to make ai generated responses despite being told not to do so see wp aitalksigns people generally don t respond well to their edits being reverted and accusations of llm use they may respond angrily be evasive about whether they used llms respond with ai generated comments attempt to wikilawyer their way around nollm or straight up lie some users may be unaware they ve been using llms as is commonly the case with grammarly or ms copilot in these instances rather than spend time and energy arguing it s usually best to explain things to them and wait to see if they make further edits using llms keep wp rope in mind if they continue to use llms after receiving thorough explanations they can be blocked whether at ani or by using ainba at ainb they may also go inactive in both cases you can peacefully proceed with cleanup some people may come from cultures that place emphasis on saving face with this causing evasiveness in these instances it s best to seek a commitment to not use llms in future rather than seek a humiliating admission of past use inline with wp preventative it s usually best to be vague about how the content was determined to be llm generated telling the editor about wp aisigns may result in them attempting to mask or superficially fix the content i e wp beans useful essays edit wikipedia help i ve been accused of using ai wikipedia honesty wikipedia do not lie about ai wikipedia responsibly using large language models wikipedia yes that does violate the ai guidelines wikipedia yes you have to follow nollm doing the cleanup edit ai cleanup is typically done on a per user basis rather than on individual articles because if someone uses llms once they re likely to use them habitually reviewing llm generated content and attempting to preserve it while ensuring wp pag compliance is time consuming and it s usually more realistic to remove such content by either stubbifying or rewriting from scratch cleanup is sometimes as simple as reverting the offending edit or restoring an earlier version though it becomes harder if the edit is old and there have been significant edits by other editors after it even sometimes to it here you can manually remove content added by the user which is still live in the article and replace it with that from the previous revision if pre existing content was overwritten or restore an earlier version while copy pasting in later significant edits who wrote that is useful for highlighting content added by the user which still remains in the article b for some additions or for when the prior version of the article is of poor quality it s worth considering salvaging basic facts from the content any pages not just articles that meet the criteria laid out at wp g15 can be tagged for speedy deletion llm generated creations can also be dealt with by draftifying and tagging with ai generated c taking them to wp afd or the presumptive removal process outlined below presumptive removal edit if a user has a history of llm use any editor can presumptively remove their edits i e without reviewing each one within a determined timeframe if the criteria at wikipedia presumptive removal of ai generated content is met this is because of the asymmetry of effort between publishing llm generated content and cleaning it up it would be extremely time consuming to review each edit and creation so as to preserve as much as possible compared to how little time it takes to generate them presumptive reverting of edits sometimes referred to as llmprv is the same process as discussed above except you don t need to prove the content set to be removed is ai generated for article creations where the llm using editor is the only significant contributor and meets certain criteria you can tag them for a special type of proposed deletion called llmprod wherein they are deleted by an admin after 5 or more days if no one removes the tag to see someone s creations scroll to the bottom of their contributions page and click articles created which takes you to xtools there is guidance on the process at wp llmprod process but it basically involves checking the page history for significant contributions from other editors and either using the excellent user dvrted ainb helper feature or copy pasting the tag and an edit summary you may want to have a page like user kowal2701 llmprod to tab to llmprods haven t been added to twinkle yet what counts as a significant contribution is subjective but this typically excludes things like copyediting or gnoming articles that do have significant contributions from others should be tagged with ai generated instead it is usually worth tagging their drafts as well to see them add 118 to the url for their list of creations on xtools if you ve llmproded a large number of articles on a single topic eg 20 you can see this in the wikiproject table on xtools although not every article will have been tagged for wikiprojects it s usually best practice to notify the relevant wikiproject s about them and ask if anyone wants to save them from deletion often the hard part of presumptive removal is determining the timeframe during which the editor used llms if an editor is clearly good faith and active you can draftify and tag their creations instead of deleting so that they can work on them if they wish and go through afc if necessary just remember to explain matters to them eg because people often underestimate the issues with ai generated content places and resources for cleanup edit ai noticeboard the main place onwiki for ai cleanup also see wp ainb backlog bonanza which focuses on potential llmprods and unresolved cases that were archived category ai noticeboard open cleanup cases a list of all the tracking subpages for open cases needing cleanup alternatively you can go through the ainb archives and do them chronologically user dvrted ainb helper a script that makes tracking subpages for cleanup eg user dvrted sandbox2 category articles containing suspected ai generated texts a category that documents articles tagged with ai generated a tool that ranks pages tagged with ai generated by number of pageviews they get special abusefilter 1407 log logs the removal of the ai generated family of tags including ai generated special abusefilter 1408 log logs the removal of prod llm tags an insite search for users that have been warned using uw ai and whose edits may need cleanup an insite search for users who have received a wp g15 notice db llm notice and may have other edits and creations needing cleanup old listings at wp dsaigen need to check the authors other creations and edits for potential cleanup user superhamster aimarker a user script that overlays identified ai generated modified images with an ai marker see wp aiimage for the relevant policy patrolling the wiki edit there are many ways to search the wiki for llm generated content see user gnomingstuff guide to finding ai generated text for an in depth guide useful tools edit wikitomte llm a tool that finds a probable llm generated content based on gnomingstuff s guide it may be worth investigating the user who added the offending content edit filter logs also mentioned above ones to monitor include 893 1030 1325 1346 1369 see for them all together recent changes filter possible ai generated citations edits for which it is near certain ai was used in some capacity recent changes filter possible formatting issues not always due to ai but strongly correlated wikipedia wikiproject deletion sorting suspected ai generated articles suspected ai generated articles at afd worth looking at the creators other creations to see if further cleanup is needed templates related to ai cleanup edit maintenance ai generated maintenance banner ai generated inline inline tag ai generated source inline tag ai retrieved source inline tag upscaled images maintenance banner upscaled inline inline tag g15 exempt to preserve ai generated pages for documentation purposes discussions collapse ai top user warnings uw ai1 uw ai2 uw ai3 uw ai4 standard warnings uw aint alternative wording uw create ai1 uw create ai2 for new article creations uw aiask for when llm use is uncertain uw aitalk1 uw aitalk2 uw aitalk3 uw aitalk4 for comments articles for creation afc submission d ai for declining drafts afc decline reason ai for notifying users speedy deletion db g15 db llm db ai for nominating a page db llm notice pagename for notifying users proposed deletion prod llm edit notice generative ai editnotice administrative uw llmblock block notice for sitewide blocks uw llmpblock block notice for partial blocks decline ai for unblock requests wikiproject ai cleanup wikiproject ai cleanup project banner user wp ai cleanup userbox user wp ai cleanup alt userbox ft wikipe tan the ai cleanup barnstar barnstar wikiproject ai cleanup topicon topicon wikiproject ai cleanup topicon alt topicon ft wikipe tan see also edit wikipedia artificial intelligence resources wikipedia wikiproject ai tools meta artificial intelligence discord invite link footnotes edit notes edit although an ai sign such as the use of emdashes wp aidash often appears in human written content as well the co occurrence of this with several other ai signs rapidly decreases the likelihood the content was human written for example if the likelihood of emdashes appearing in human written content was say 20 and that of say the words pivotal and interplay wp aivocab and over attribution wp aiattr was 15 and 25 respectively the likelihood of the content being human written if these three signs appear simultaneously drops to only 0 75 diffundo can be used to restore the pre existing text if any had been overwritten while keeping edits after it intact to use diffundo go to the revision before the offending edit s by clicking its timestamp click edit click show changes then undo all lines except those added by the user before clicking publish user mpguy2824 movetodraft is useful because it automatically tags the mainspace redirect for speedy deletion wp r2 rather than you having to do it manually references edit cheng adam lin yiqun reedy gabriel joseph christine wirkowski samantha mallette viviane nagesh vikhashni krieser david calhoun aaron 2025 ability of ai detection tools and humans to accurately identify different forms of ai generated written content advances in simulation 10 1 66 doi 10 1186 s41077 025 00396 6 pmc 12752165 pmid 41272826 russell jenna karpinska marzena iyyer mohit 2025 people who frequently use chatgpt for writing tasks are accurate and robust detectors of ai generated text proceedings of the 63rd annual meeting of the association for computational linguistics volume 1 long papers vienna austria association for computational linguistics pp 5342 5373 arxiv 2501 15654 doi 10 18653 v1 2025 acl long 267 archived from the original on 2025 08 29 retrieved 2025 09 05 via acl anthology fowler geoffrey august 14 2023 what to do when you re accused of ai cheating the washington post retrieved october 20 2023 people who frequently use chatgpt for writing tasks are accurate and robust detectors of ai generated text arxiv org retrieved 2025 11 28 retrieved from https en wikipedia org w index php title wikipedia wikiproject_ai_cleanup guide_and_resources oldid 1374860939 categories wikiproject advice wikiproject ai cleanup this page was last edited on 14 september 2026 at 13 42 utc page was rendered with parsoid text is available under the creative commons attribution shareali...