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Antislop: A framework for eliminating repetitive patterns in language models
- DarmokJalad1701 1y agoYou're absolutely right!
- kridsdale1 1y agoWhat a brilliant observation you’ve made.
- _cenw 1y agoThis is such a nuanced view on things!
- mrbungie 1y agoI don't know if not getting the idea right, but I'm pretty sure people refer to AI outputs as "slop" not due to (only) repetitiveness. According to some sources: [1] Wikipedia > AI slop is digital content made with generative artificial intelligence, specifically when perceived to show a lack of effort, quality or deeper meaning, and an overwhelming volume of production.[1][4][5] Coined in the 2020s, the term has a pejorative connotation similar to spam.[4] [2] Urban dictionary > Low-quality randomly generated AI content (images, accounts, text, etc) that has been flooding social media sites among other pages. Yes, I know those may not be the best primary sources, but I'd say the main shared meaning of the word is lack of quality and effort, not repetitiveness itself. [1] https://en.wikipedia.org/wiki/AI_slop https://en.wikipedia.org/wiki/AI_slop [2] https://www.urbandictionary.com/define.php?term=AI+slop https://www.urbandictionary.com/define.php?term=AI+slop
- yawnxyz 1y agoHonestly "slop" should also be retroactively applied to e.g. Buzzfeed content; it shouldn't just be AI-centric
- louthy 1y agoIt isn’t AI centric, it’s derived from poor quality wet food. Often given to pigs or used to describe prison food. It’s the origin of the term ‘sloppy’. Colloquially it means ‘poor quality’ and always has done. So buzzfeed is journalism slop, just like poor quality AI content is AI slop.
- jsheard 1y agoYeah, what this actually achieves if anything is making it harder to quickly recognize slop for what it is, so readers are more likely to give it the benefit of the doubt and keep their eyeballs on it for longer. Which I suppose is desirable if you're in the slop-mongering business (e.g. doing SEO spam or other such methods of flooding the commons with sewage for the sake of profit).
- mrbungie 1y agoYep, and their only reference to the word points to a survey that does not mention slop even once (A survey onllm-generated text detection: Necessity, methods, and future directions. Computational Linguistics, 51(1):275–338, 2025., https://arxiv.org/abs/2310.14724 https://arxiv.org/abs/2310.14724) That's sloppy (hehe), if you are going to redefine a common word for the first time (i.e. references are not possible) at least do it explicitly.
- moritzwarhier 1y agoFits into a broad pattern of deceptive LLM terminology, for example "Deep Research": a humble and honest moniker would me "Reflection" or "Recursive self-prompting".
- the8472 1y agoGain-of-function research to create memetic-immune-system-evading AI variants. > Ethics Statement > Potential harms include: [...] (ii) attempts to evade AI-text detection. And it's not clear to me how their mitigations would avoid fooling users (as opposed to algorithmic detection attempts).
- iahds9uasd 1y agoThe LLM erotic roleplaying community's usage of "slop" aligns with the definition in this paper, so it's not without precedent. Several novel sampling methods have originated from that community trying to address this specific issue.
- Der_Einzige 1y agoYup. You see this with the very first projects to get a new sampler being oobabooga text gen webui, sillytavern circa early 2023 with min_p. Same with diffusion models. First projects to get new denoising algorithms are ComfyUI, Automatic1111, etc.
- mrbungie 1y agoNothing wrong with that, but at (1) least reference it or (2) define it yourself explicitly.
- palmotea 1y ago> I don't know if not getting the idea right, but I'm pretty sure people refer to AI outputs as "slop" not due to (only) repetitiveness. According to some sources: Yeah, slop is low effort use of AI output ("ChatGPT, write me a blog post about using AI in industry X. Copy. Paste. Publish."). If anything this is should be called Stealthslop, and when slop is harder to detect we'll all waste more time on it.
- ottah 1y agoIn practice, it's used for anything the speaker doesn't approve of, regardless of quality. When someone uses it, it basically tells me, I don't have anything critical to say, beyond I don't like a thing.
- topaz0 1y agoI came here to say this -- it's going to be slop no matter what.
- calvinmorrison 1y agowe're calling it compu-slop
- deleted 1y ago[deleted]
- sixwing 1y agoi took a swing at an anti-slop skill for Claude Code, this week: https://github.com/rand/cc-experiments/tree/main/skills/anti-slop https://github.com/rand/cc-experiments/tree/main/skills/anti...
- growdark 1y agoDoes this actually work or would the slop just become more subtle?
- atourgates 1y agoI've been using ChatGPT fairly regularly for about a year. Mostly as an editor/brainstorming-partner/copy-reviewer. Lots of things have changed in that year, but the things that haven't are: * So, so many em-dashes. All over the place. (I've tried various ways to get it to stop. None of them have worked long term). * Random emojis. * Affirmations at the start of messages. ("That's a great idea!") With a brief pause when 5 launched. But it's back and worse than ever now. * Weird adjectives it gets stuck on like "deep experience". * Randomly bolded words. Honestly, it's kind of helpful because it makes it really easy to recognize content that people have copied and pasted out of ChatGPT. But apart from that, it's wild to me that a $500bn company hasn't managed to fix those persistent challenges over the course of a year.
- neoCrimeLabs 1y agoI am reasonably sure affirmations are a feature, not a bug. No matter how much I might disagree.
- illuminator83 1y agoAlso pretty sure it is a feature because the general population wants to have pleasant interactions with their ChatGPT and OpenAI's user feedback research will have told them this helps. I know some non-developer type people which mostly talk to ChatGPT about stuff like - how to cope with the sadness of losing their cat - ranting about the annoying habits of their friends - finding all the nice places to eat in a city etc. They do not want that "robot" personality and they are the majority.
- neoCrimeLabs 1y agoAgreed on all points. I also recall reading a while back that it's also a dopamine trigger. If you make people feel better using your app, they keep coming back for another fix. At least until they realize the hollow nature of the affirmations and start getting negative feelings about it. Such a fine line.
- giancarlostoro 1y ago
- SoftTalker 1y agoI honestly can’t always distinguish AI slop from the formulaic corp-speak used in emails and memos and brochure websites and other marketing. I’m guessing that must be a large component of the training matter.
- cyanydeez 1y agoI'd say the majority of the training data is reddit with zero care about whether it's from a "good" or "sarcastic" or "ironic" source.
- watwut 1y agoThat is because corp speak is usually management-slop. A content devoid of ... content whose whole purpose is to make the author look important.
- vintermann 1y agoI don't think that's a coincidence. Right now a lot of the business proposition for LLM bots is selling it to corporations as the ultimate corporate yes-man.
- Babkock 1y ago[flagged]
- artninja1988 1y ago[flagged]
- jjangkke 1y agoThere will be an intersection when the techniques and continued refinements in making tall tale signs of AI and new powerful model meets where it becomes very time consuming, expensive and difficult to tell between human generated and AI generated content. We are already at a point where we can trick large number of the population, it can without a doubt close the gap even further where we question anything and everything. Beyond forensics, which require large capital investment and operating costs, to be able to detect AI vs human content will be limited in terms of access. It will be so that its not that we can't detect AI content anymore its that most people cannot afford the service to detect it and thus they lose interest. This has side effect of making live performances by humans scarce and in valuable.
- teeray 1y ago> This has side effect of making live performances by humans scarce and in valuable. RIP take-home coding assignments.
- mrbungie 1y agoAlso RIP any take-home assignment that depends at least partially on writing prose/essays. Schools will need to reinvent themselves in some ways.
- sorokod 1y agoThat narrowing gap is where we humans find purpose and meaning. If an impersonation of an opera singer can't be distinguished from the real thing, what would be the point of the real thing?
- meowface 1y agoSlop is a much more general concept than that. I wish they would've picked a different term. "LLM fluff phrases" or something.
- layer8 1y agodiction, phraseology
- growdark 1y agoI'd love to see a benchmark that tests different LLMs for slop, not necessarily limited to code. That might be even more interesting than ARC-AGI.
- jampa 1y agoNot a benchmark per se, but there is a "Not x, but y" Slop Leaderboard: https://www.reddit.com/r/LocalLLaMA/comments/1lv2t7n/not_x_but_y_slop_leaderboard/ https://www.reddit.com/r/LocalLLaMA/comments/1lv2t7n/not_x_b...
- Bolwin 1y agoSee the writing benchmarks here https://eqbench.com/creative_writing_longform.html https://eqbench.com/creative_writing_longform.html
- Der_Einzige 1y agoNote this is the same first author
- deleted 1y ago[deleted]
- topaz0 1y ago100% of LLM output is slop. Done.
- skywhopper 1y agoThat’s not what “slop” means. Slop is output produced by generative AI without regards to its quality, not the telltale tics that current models tend to exhibit.
- tartoran 1y agoYep. Sanitized slop is still slop.
- Lerc 1y ago>That’s not what “slop” means It's a new term so the meaning hasn't had a chance to settle. It's generally considered to be a negative term, so there's motivation for people to expand the definition to include things that they don't like. It is much easier to subvert a category than it is to make an argument for an individual item. Imagine if people accept that falling rocks kill hundreds of people every year, and you wanted to convince them that falling cheese also kills plenty of people. It would be much easier to imply that cheese, often coming in large roundish lumps, counts as a type of rock. It stretches the definition a bit but it's still much easier to argue than the actual falling cheese argument that is your actual agenda. When the definition is new it is more malleable. Sometimes you might need a qualifier to declare it is different but imply it is essentially like the other thing. It's just a dairy-rock, or just enhanced-interrogation.
- hatthew 1y agoI've seen it used enough that it's clear to me that the implied definition is "low-quality and/or low effort AI-generated content", and the actual usage is "AI generated content that I don't like". But both of those definitions very clearly refer to the piece of content as a whole, rather than specific parts of the content.
- ottah 1y agoSlop is what you make, when I don't morally approve, or value critical nuance. WWE is slop, soap operas are slop, romance novels are slop, scifi is slop, etc.
- voldacar 1y agoInstead of "surgically adjusting" logits within an existing model, couldn't you just build the slop detector into the loss function during the initial training stage?
- westurner 1y agoScholarlyArticle: "Antislop: A Comprehensive Framework for Identifying and Eliminating Repetitive Patterns in Language Models" (2025) https://arxiv.org/abs/2510.15061 https://arxiv.org/abs/2510.15061 : > Abstract: [...] Our approach combines three innovations: (1) The Antislop Sampler, which uses backtracking to suppress unwanted strings at inference time without destroying vocabulary; (2) An automated pipeline that profiles model-specific slop against human baselines and generates training data; (3) Final Token Preference Optimization (FTPO), a novel fine-tuning method that operates on individual tokens, surgically adjusting logits wherever a banned pattern has appeared in an inference trace. From https://news.ycombinator.com/item?id=45546037#45585680 https://news.ycombinator.com/item?id=45546037#45585680 , an additional potential method: >> Could build a simple heuristic: if similar memory content gets created/updated N times within short timeframe, flag it as potential loop
- orbital-decay 1y agoThis seems to be fundamentally based on n-grams and manually built regexes. "Slop", or more narrowly annoying -isms and model stereotypes, is not just repetitive n-gram sequences, mode collapse manifests itself semantically. Sometimes repetition/stereotyping is desirable (you need semantics to understand if it's the case), and sometimes undesirable repetition is undetectable by n-grams and regexes, especially in languages that rely on word formation. Fixing the mode collapse probably needs a sufficiently powerful reference model of semantic diversity, which doesn't currently exist.
- Lucian6 1y ago[dead]
- topaz0 1y agoEasy -- turn off the computer and have a competent human do the interview
- razodactyl 1y agoYep. Not all situations need a sledgehammer. Especially ones with such nuance.
- arresin 1y agoChatgpt-5: Oof—-gotcha here’s how I’d handle that Clutch choice—-here’s a few refinements Sweet—-let me just… Ok, here’s the receipts I love your passion! Let’s try to keep it civil ok? (Thinking) the user still appears annoyed —————————————- I think this annoys them also and yet they can’t change it? Or are they not dogfooding?
- cindyllm 1y ago[dead]
- gwern 1y agoThis is the epitome of patching symptoms rather than treating the disease. Even if you suppress the obvious syntactic slop like 'it's not X but Y', you have no reason to believe you've fixed mode-collapse on higher more important levels like semantics and creativity. (For example, Claude LLMs have always struck me as mode-collapsed on a semantic level: they don't have the blatant verbal tics of 4o but somehow they still 'go in circles'.) Which will potentially severely hinder the truly high-value applications of LLMs to creative applications like frontier research. To the extent that this succeeds in hiding the brain damage in contemporary LLMs, it arguably is a cure worse than the disease.
- Der_Einzige 1y agoWow it’s pretty sad to see one of my idols be kind of a hater on this. :(
- razodactyl 1y agoHow come? It was a valid take on the situation. Critical feedback is vital to success.
- sam-paech 1y agoThose higher level kinds of mode collapse are hard to quantify in an automated way. To fix that, you would need interventions upstream, at pre & post training. This approach is targeted to the kinds of mode collapse that we can meaningfully measure and fix after the fact, which is constrained to these verbal tics. Which doesn't fix higher level mode collapse on semantics & creativity that you're identifying -- but I think fixing the verbal tics is still important and useful.
- gwern 1y ago> but I think fixing the verbal tics is still important and useful. I don't. I think they're useful for flagging the existence of mode-collapse and also providing convenient tracers for AI-written prose. Erasing only the verbal tics with the equivalent of 's/ - /; /g' (look ma! no more 4o em dashes!) is about the worst solution you could come up with and if adopted would lead to a kind of global gaslighting. The equivalent of a vaccine for COVID which only suppresses coughing but doesn't change R, or fixing a compiler warning by disabling the check. If you wanted to do useful research here, you'd be doing the opposite. You'd be figuring out how to make the verbal expressions even more sensitive to the underlying mode-collapse, to help research into fixing it and raising awareness. (This would be useful even on the released models, to more precisely quantify their overall mode-collapse, which is poorly captured by existing creative writing benchmarks, I think, and one reason I've had a hard time believing things like Eqbench rankings.)
- simianwords 1y agoHow well does this work for higher level slop? Sure it can eliminate the em dash but can it eliminate smells at paragraph level?
- EigenLord 1y agoInteresting work but this strikes me as a somewhat quixotic fight against inevitable tendencies of statistical models. Reinforcement learning has a single goal, an agreeable mean. Reinforcement learning stops when the LLM produces agreeable responses more often than not, the only way you can achieve absolute certainty here is if you tune it for an infinite amount of time. I also don't see how this method couldn't be subsumed by a simpler method like dynamic temperature adjustment. Transformers are fully capable of generating unpredictable yet semantic text based on a single hyperparameter. Maybe it would make more sense to simply experiment with different temperature settings. Usually it's a fixed value.
- BAPHOMETA88F 1y agoParsing a LLM as the measure of a series of qc metrics, which isolate for preference strings, whether lexical weights or parameters. Can this create the rules for formal understanding or correlating libraries of Babel? Searle's paper calls these questions, script, or a story. [1]:https://web.archive.org/web/20071210043312/http://members.aol.com/NeoNoetics/MindsBrainsPrograms.html https://web.archive.org/web/20071210043312/http://members.ao...
- teddyh 1y agoHere’s an anti-slop filter, applicable to all AI text: sed -e d
- ath3nd 1y ago[dead]