arxiv.org/abs/2406.12934
link.springer.com/chapter/10.1...
What are these, really? And each of them already has nearly a hundred citations.
Perhaps, to some degree, actually reading papers before citing them would be a good way to avoid giving credit where it is not deserved.
I am seeing more and more papers on AI that feel ChatGPT-written, or at least heavily assisted by ChatGPT. They are designed to include the **right** buzzwords like "AI sycophancy" or "AI guardrails" to get citations while offering very low-quality content and sometimes even false information.
Great conversation with Mirta on belief dynamics!
www.youtube.com/watch?v=3rol...
When the problem is so "obstruse" you gotta start praying
Two-panel figure showing example Civitai bounty pages. Panel (a) displays the ``Civitai Official Bounty - Swamp Monster Style LoRA'' bounty page featuring two unblurred fantasy creature images: a moss-covered humanoid creature and a colorful frog-like monster with large eyes. The bounty details show it's a LoRA creation type, base model SD 1.5, started October 16, 2023, with deadline October 23, 2023. A completion banner indicates prizes have been awarded to winners. The supporter section shows a user avatar with a 50,000 buzz reward. Panel (b) shows ``Dno's 2k Special'' bounty page with two blurred images of different content ratings - one marked as R with a ``Show'' button overlay, and another marked as XXX with a ``Show'' button. The bounty type is image creation, started September 22, 2025, with deadline October 23, 2025. Supporter names are redacted for privacy.
Four-panel figure showing Civitai bounty statistics. Panel (a) shows a horizontal bar chart of bounty counts by type, with LoRA having the most bounties at 2,984, followed by Image at 1,475, Model at 138, and decreasing to Video at 35. Panel (b) displays a horizontal bar chart of bounty themes by proportion, with NSFW being the largest category at approximately 0.43 (comprising 2,286 bounties split between platform-labeled and GPT-4.1 classified NSFW shown with diagonal hatching), followed by Fictional Characters at 1,463 bounties. Panel (c) presents stacked horizontal bars showing NSFW versus SFW proportions for each bounty type, with Video being 69\% NSFW and Embed being 82\% SFW. Panel (d) shows a time series from November 2023 to January 2025 displaying the proportion of SFW (decreasing trend line) and NSFW (increasing trend line) bounties over time, with 95\% confidence intervals shown as shaded regions around each trend line and vertical dashed lines marking the start of 2024 and 2025.
Two-panel figure analyzing deepfake bounties on Civitai. Panel (a) shows gender distribution split into two horizontal bar charts. The top chart displays NSFW deepfake bounties with Female at 95.8\% and Male at 4.2\%. The bottom chart shows SFW deepfake bounties with Female at 89.6\%, Male at 10.1\%, and Non-binary at 0.3\%. Panel (b) presents a stacked horizontal bar chart showing the profession distribution across all deepfakes, with bars color-coded for NSFW (red) and SFW (blue) categories. Actor/actress leads at 39.3\% of deepfakes, followed by Influencer at 13.9\%, Adult worker at 13.0\%, Artist at 10.2\%, Miscellaneous at 8.4\%, Model at 7.4\%, Athlete at 5.3\%, Self/spouse at 1.2\%, Reporter at 0.9\%, and Producer at 0.3\%. The x-axis shows the number of bounties ranging from 0 to 140.
🚨 New working paper 🚨
What happens when you add money + competition to generative AI creation?
On Civitai—a prominent platform for gen-AI content/tools w. millions of users—you get a growing marketplace for NSFW requests and a nontrivial stream of deepfakes.
Preprint: arxiv.org/abs/2601.09117 🧪
Thanks! Yeah, seems like they could be information operations. Our lab has been working on detecting such activity but I always wondered if having IP addresses etc. would help detection. Some example papers:
epjds.epj.org/articles/epj...
ojs.aaai.org/index.php/IC...
Interesting. What do you mean by network? and how do you infer the geographical area?
Very exciting talk in two weeks! Join us if you want to learn about dynamics of belief networks.
Cool paper showing how LLMs can be corrupted.
"We train a model on benevolent goals that match the good Terminator character from Terminator 2. Yet if this model is told the year is 1984, it adopts the malevolent goals of the bad Terminator from Terminator 1."
arxiv.org/abs/2512.09742
🚨 A research staff position at my group at @uvadatascience.bsky.social!
I’m recruiting a research Scientist (or postdoc scholar). You can apply here! bit.ly/ylab-researc...
For more information: www.linkedin.com/feed/update/...
Inquiries: yyahn@virginia.edu with [job] in the subject line.
Can't wait for the second episode!
Since these reports are likely to be influential, citing this paper may indirectly lend it more credibility than it deserves.
Hi Yoshua, thank you for sharing the reports. I wanted to flag something in the arXiv version of the AI Safety report (arxiv.org/abs/2510.13653). I suspect that one of the cited papers might be mostly AI-generated, as it has ghost citations and questionable references: arxiv.org/abs/2411.15287
New paper 🧪
We propose a field experiment to study the effects of friction interventions for curbing the spread of misinformation. ABM simulations suggest that when combined with learning, friction could significantly increase average post quality
doi.org/10.1038/s442...
We're wrapping up the semester with THREE OSoMe Awesome Speakers!
📅 November 12 @ 12 PM ET
Petter Törnberg, University of Amsterdam
📅 November 19 @ 12 PM ET
Michelle Amazeen, Boston University
📅 December 3 @ 12 PM ET
James Evans, University of Chicago
Register: osome.iu.edu/events/speak...
Thank you for the article! AI "resonating" with people has been another problem we should definitely think more of www.nytimes.com/2025/08/08/t...
Kudos to my wonderful advisors and coworker who made this paper possible! @baottruong.bsky.social @alessandroflammini @fil.bsky.social 🙏
We propose that "constructive conflicts" can model healthier, "bridging" content 🌉 But, “destructive conflicts" shouldn't be ignored but approached with careful linguistic choices to transform toxic arguments into productive dialogues.
Since destructive conflicts are too important to ignore, we analyze their language 🔍 We find that how something is said matters immensely. Civil language (asking questions, providing detail, and using hedges) makes posts far more resilient to toxicity, while negative language has the opposite effect
- Destructive conflicts 🪖 (high C & high TA, panel c) focus on polarizing identity issues like abortion and LGBTQ+ rights.
- Constructive conflicts 🕊️ (high C & low TA, panel d) spark civil debate on policy topics like student loans, AI, and marijuana legalization.
To identify constructive conflict, we train two models to score posts based on their likelihood of attracting toxic comments - which we call toxicity attraction (TA) model - and their controversiality - (C) model 💻 Plotting the scores inferred by these models shows clear patterns.
We find that a post doesn't need to be toxic to attract toxic comments ☢️ Our Reddit data shows that 47% of non-toxic submissions still attract at least one toxic reply, while only 6% of toxic submissions do. The initial post's content, therefore, is a poor predictor of a comment section's health.
In our research, we argue that the key lies in identifying constructive conflict — controversial posts that are toxicity resilient. We define a "toxicity resilient" post as one that is less likely to attract toxic responses from other users. See our #ICWSM2026 paper here arxiv.org/abs/2509.18303 📖
A simple solution, prioritizing only “the feel-good" content, is flawed, as it avoids important societal topics that are inherently negative and can devolve into toxic debates. After all, how often does thinking about wars, viruses, or economic policy put a smile on your face?
Modern social media is divisive, partly due to recommender algorithms that promote emotionally charged, negative content at the expense of thoughtful discourse. Researchers are exploring prosocial recommenders that foster positive outcomes, aiming for users to feel connected rather than angry 💡
#ic2s2 let's connect! If we had a conversation and I haven't followed you yet, please do follow!
@ic2s2.bsky.social 2025 was amazing! Thanks to all the committee members for organizing.
I had a chance to present my recent work, met some brilliant people, got star struck a few times, had great feedback, experienced Sweden, and got to catch up with my academic father :) couldn't ask for more!
The Effects of Outgroup Agreement and Ingroup Dissent on Political Polarization
📍 Talk | Jul 24, 11:00 AM | Troselli
Scaling of Community Rules Across Mastodon Servers
📍 Talk | Jul 24, 11:00 AM | Vingen 3+4
#ic2s2
