Tootfinder

Hollywood insiders report widespread off-the-books AI experimentation in studios, often hidden due to avoid backlash, despite union contracts limiting AI use (Lila Shapiro/Vulture)
https://www.vulture.com/article/generative-ai-hollywood-movies-tv.html…

Hollywood Already Uses Generative AI (And Is Hiding It)
With dozens of new studios and rapidly evolving tech, generative AI video is more embedded in Hollywood movies and TV than we may realize.

Hollywood insiders report widespread off-the-books AI experimentation in studios, often hidden due to avoid backlash, despite union contracts limiting AI use (Lila Shapiro/Vulture)
https://www.vulture.com/article/generative-ai-hollywood-movies-tv.html…

Hollywood Already Uses Generative AI (And Is Hiding It)
With dozens of new studios and rapidly evolving tech, generative AI video is more embedded in Hollywood movies and TV than we may realize.

Generative AI, Copyright, and Market Harm – Copyhype https://www.copyhype.com/2025/05/generative-ai-copyright-and-market-harm/?utm_source=dlvr.it&ut…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
Mohammad Saleh Torkestani, Taha Mansouri
https://arxiv.org/abs/2506.02046 https:…

Machine vs Machine: Using AI to Tackle Generative AI Threats in Assessment
This paper presents a theoretical framework for addressing the challenges posed by generative artificial intelligence (AI) in higher education assessment through a machine-versus-machine approach. Large language models like GPT-4, Claude, and Llama increasingly demonstrate the ability to produce sophisticated academic content, traditional assessment methods face an existential threat, with surveys indicating 74-92% of students experimenting with these tools for academic purposes. Current respon…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/5]:
- Learning Traffic Anomalies from Generative Models on Real-Time Observations
Fotis I. Giasemis, Alexandros Sopasakis

This https://arxiv.org/abs/2505.21677 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

What happens when generative AI models train recursively on each others' generated outputs?
The internet is full of AI-generated content while also serving as a common source of training data for generative AI (genAI) models. This duality raises the possibility that future genAI models may be trained on other models' generated outputs. Prior work has studied consequences of models training on their own generated outputs, but limited work has considered what happens if models ingest content produced by other models. Given society's increasing dependence on genAI tools, understanding do…

A Reference Architecture for Gamified Cultural Heritage Applications Leveraging Generative AI and Augmented Reality
Federico Martusciello, Henry Muccini, Antonio Bucchiarone
https://arxiv.org/abs/2506.04090

A Reference Architecture for Gamified Cultural Heritage Applications Leveraging Generative AI and Augmented Reality
The rapid advancement of Information and Communication Technologies is transforming Cultural Heritage access, experience, and preservation. However, many digital heritage applications lack interactivity, personalization, and adaptability, limiting user engagement and educational impact. This short paper presents a reference architecture for gamified cultural heritage applications leveraging generative AI and augmented reality. Gamification enhances motivation, artificial intelligence enables ad…

AMC signs a deal with Runway to use its tech to generate marketing images and pre-visualize unproduced shows, the first cable player to work with Runway (Steven Zeitchik/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

AMC Networks Inks Deal With AI Company Runway (Exclusive)
The ‘Mad Men’ and 'The Walking Dead' platform is the latest Hollywood company to sign a pact with the generative AI firm.

https://bobbyhiltz.com/posts/2025/06/ai-replace/index.html

AMC signs a deal with Runway to use its AI tech to generate marketing images and pre-visualize unproduced shows, the first cable player to work with Runway (Steven Zeitchik/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

AMC Networks Inks Deal With AI Company Runway (Exclusive)
The ‘Mad Men’ and 'The Walking Dead' platform is the latest Hollywood company to sign a pact with the generative AI firm.

Unpacking Graduate Students' Learning Experience with Generative AI Teaching Assistant in A Quantitative Methodology Course
Zhanxin Hao, Haifeng Luo, Yongyi Chen, Yu Zhang
https://arxiv.org/abs/2506.02966

Unpacking Graduate Students' Learning Experience with Generative AI Teaching Assistant in A Quantitative Methodology Course
The study was conducted in an Advanced Quantitative Research Methods course involving 20 graduate students. During the course, student inquiries made to the AI were recorded and coded using Bloom's taxonomy and the CLEAR framework. A series of independent sample t-tests and poisson regression analyses were employed to analyse the characteristics of different questions asked by students with different backgrounds. Post course interviews were conducted with 10 students to gain deeper insights int…

'...a student might hear "don't use generative AI" from a prof but then log on to the university's Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing'
https://www.404media.co/teachers-are-not-ok-ai-chatgpt/…

Teachers Are Not OK
AI, ChatGPT, and LLMs "have absolutely blown up what I try to accomplish with my teaching."

There's no putting the genie back in the bottle, but education is [yet another part of our society that is] completely unprepared to deal with generative AI.
Teachers Are Not OK
https://www.404media.co/teachers-are-not-ok-ai-chatgpt/

"GenAI art has already reached polyester status, and this is just the beginning. Despite all the techno-utopian promises, our brains see it as ersatz."
(Original title: GenAI is Our Polyester)
https://culture.ghost.io/genai-is-our-polyester/

GenAI is Our Polyester
The best way to understand generative AI art and aesthetics is to consider how previous "synthetics" lost value in the long-run For the first half of the 20th century, white-collar workers wore business shirts made from cotton or linen that wrinkled in the wash. Ironing them into a presentable shape

Generative AI for Multiple Choice STEM Assessments
Christina Perdikoulias, Chad Vance, Stephen M. Watt
https://arxiv.org/abs/2506.02094 https://

Generative AI for Multiple Choice STEM Assessments
Artificial intelligence technology enables a range of enhancements in computer-aided instruction, from accelerating the creation of teaching materials to customizing learning paths based on learner outcomes. However, ensuring the mathematical accuracy and semantic integrity of generative AI output remains a significant challenge, particularly in STEM disciplines. In this study, we explore the use of generative AI in which "hallucinations" -- typically viewed as undesirable inaccuracies -- can i…

Students, THIS is how generative AI (ChatGPT et alia) "reads" papers and "understands" content. It's a bullshit machine, a gaslighting machine. It shows the linguistic behavior of a psychopath (is this what us humans average to, if one trains on all our "content" and online behavior?). Yikes.
https://amandaguinzburg.substack.com/p/diabolus-ex-machina

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and this more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of manservant caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

AI-Empowered Channel Generation for IoV Semantic Communications in Dynamic Conditions
Hao Liu, Bo Yang, Zhiwen Yu, Xuelin Cao, George C. Alexandropoulos, Yan Zhang, Chau Yuen
https://arxiv.org/abs/2507.02013

AI-Empowered Channel Generation for IoV Semantic Communications in Dynamic Conditions
The Internet of Vehicles (IoV) transforms the transportation ecosystem promising pervasive connectivity and data-driven approaches. Deep learning and generative Artificial Intelligence (AI) have the potential to significantly enhance the operation of applications within IoV by facilitating efficient decision-making and predictive capabilities, including intelligent navigation, vehicle safety monitoring, accident prevention, and intelligent traffic management. Nevertheless, efficiently transmitt…

💡NFDI4Culture schreibt für die Teilnahme an der Konferenz / Autumn School "Synthetic Imaginaries: The Cultural Politics of Generative AI” (8.– 12.09.2025 an der Universität Siegen) mehrere Reisestipendien für Nachwuchswissenschaftler:innen aus, um neue Forschungsperspektiven zum Thema Generative KI zu fördern und die interdisziplinäre Vernetzung in diesem Forschungsfeld zu unterstützen.
👉 Weitere Infos findet ihr hier:

This https://arxiv.org/abs/2307.14634 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Fact-Checking of AI-Generated Reports
With advances in generative artificial intelligence (AI), it is now possible to produce realistic-looking automated reports for preliminary reads of radiology images. This can expedite clinical workflows, improve accuracy and reduce overall costs. However, it is also well-known that such models often hallucinate, leading to false findings in the generated reports. In this paper, we propose a new method of fact-checking of AI-generated reports using their associated images. Specifically, the dev…

This https://arxiv.org/abs/2505.24584 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

AutoChemSchematic AI: A Closed-Loop, Physics-Aware Agentic Framework for Auto-Generating Chemical Process and Instrumentation Diagrams
Recent advancements in generative AI have accelerated the discovery of novel chemicals and materials; however, transitioning these discoveries to industrial-scale production remains a critical bottleneck, as it requires the development of entirely new chemical manufacturing processes. Current AI methods cannot auto-generate PFDs or PIDs, despite their critical role in scaling chemical processes, while adhering to engineering constraints. We present a closed loop, physics aware framework for the…

Computer Science Education in the Age of Generative AI
Russell Beale
https://arxiv.org/abs/2507.02183 https://arxiv.org/pdf/2507.0218…

Computer Science Education in the Age of Generative AI
Generative AI tools - most notably large language models (LLMs) like ChatGPT and Codex - are rapidly revolutionizing computer science education. These tools can generate, debug, and explain code, thereby transforming the landscape of programming instruction. This paper examines the profound opportunities that AI offers for enhancing computer science education in general, from coding assistance to fostering innovative pedagogical practices and streamlining assessments. At the same time, it highl…

Looked at latest W3C Draft of “Accessibility of machine learning and generative AI,” specifically the overlays section:
https://w3c.github.io/ai-accessibility/#accessibility-overlays
I still think it needs to be stricken:

This https://arxiv.org/abs/2405.08965 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Meaning-Typed Programming: Language Abstraction and Runtime for Model-Integrated Applications
Software development is shifting from traditional logical programming to model-integrated applications that leverage generative AI and large language models (LLMs) during runtime. However, integrating LLMs remains complex, requiring developers to manually craft prompts and process outputs. Existing tools attempt to assist with prompt engineering, but often introduce additional complexity. This paper presents Meaning-Typed Programming (MTP) model, a novel paradigm that abstracts LLM integratio…

Generative AI and the future of scientometrics: current topics and future questions
Benedetto Lepori, Jens Peter Andersen, Karsten Donnay
https://arxiv.org/abs/2507.00783

Generative AI and the future of scientometrics: current topics and future questions
The aim of this paper is to review the use of GenAI in scientometrics, and to begin a debate on the broader implications for the field. First, we provide an introduction on GenAI's generative and probabilistic nature as rooted in distributional linguistics. And we relate this to the debate on the extent to which GenAI might be able to mimic human 'reasoning'. Second, we leverage this distinction for a critical engagement with recent experiments using GenAI in scientometrics, including topic lab…

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Zosia Krusberg
https://arxiv.org/abs/2506.00229 http…

Where's the Line? A Classroom Activity on Ethical and Constructive Use of Generative AI in Physics
Generative AI tools like ChatGPT are rapidly reshaping how students and instructors engage with course material-and how they think about academic integrity. This paper presents a classroom activity designed to help physics students critically examine the ethical and educational implications of using AI in coursework. Through a structured sequence of case analysis, discussion, and optional policy drafting, students develop the metacognitive, ethical, and collaborative skills needed to navigate e…

This https://arxiv.org/abs/2412.00639 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Needle: A Generative AI-Powered Multi-modal Database for Answering Complex Natural Language Queries
Multi-modal datasets, like those involving images, often miss the detailed descriptions that properly capture the rich information encoded in each item. This makes answering complex natural language queries a major challenge in this domain. In particular, unlike the traditional nearest neighbor search, where the tuples and the query are represented as points in a single metric space, these settings involve queries and tuples embedded in fundamentally different spaces, making the traditional que…

Agentic AI and Multiagentic: Are We Reinventing the Wheel?
V. Botti
https://arxiv.org/abs/2506.01463 https://arxiv.org/pdf/2506.01463…

Agentic AI and Multiagentic: Are We Reinventing the Wheel?
The terms Agentic AI and Multiagentic AI have recently gained popularity in discussions on generative artificial intelligence, often used to describe autonomous software agents and systems composed of such agents. However, the use of these terms confuses these buzzwords with well-established concepts in AI literature: intelligent agents and multi-agent systems. This article offers a critical analysis of this conceptual misuse. We review the theoretical origins of "agentic" in the social science…

This https://arxiv.org/abs/2504.07879 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Towards Sustainable Creativity Support: An Exploratory Study on Prompt Based Image Generation
Creativity is a valuable human skill that has long been augmented through both analog and digital tools. Recent progress in generative AI, such as image generation, provides a disruptive technological solution to supporting human creativity further and helping humans generate solutions faster. While AI image generators can help to rapidly visualize ideas based on user prompts, the use of such AI systems has also been critiqued due to their considerable energy usage. In this paper, we report on …

"it feels like the hope with generative AI is that no matter how much you may hate it, the goal is to bombard you with its horrors and its excesses so frequently that you become numb to it."
(Original title: I’m Getting Real Tired Of Not Being Able To Trust That A Video Game Doesn’t Have AI Crap In It)
https://

I'm Getting Real Tired Of Not Being Able To Trust That A Video Game Doesn't Have AI Crap In It - Aftermath
It sucks that players are having to scour every asset and line of dialogue

Searching Clinical Data Using Generative AI
Karan Hanswadkar, Anika Kanchi, Shivani Tripathi, Shi Qiao, Rony Chatterjee, Alekh Jindal
https://arxiv.org/abs/2505.24090

Searching Clinical Data Using Generative AI
Artificial Intelligence (AI) is making a major impact on healthcare, particularly through its application in natural language processing (NLP) and predictive analytics. The healthcare sector has increasingly adopted AI for tasks such as clinical data analysis and medical code assignment. However, searching for clinical information in large and often unorganized datasets remains a manual and error-prone process. Assisting this process with automations can help physicians improve their operationa…

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

This https://arxiv.org/abs/2502.14708 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Human Misperception of Generative-AI Alignment: A Laboratory Experiment
We conduct an incentivized laboratory experiment to study people's perception of generative artificial intelligence (GenAI) alignment in the context of economic decision-making. Using a panel of economic problems spanning the domains of risk, time preference, social preference, and strategic interactions, we ask human subjects to make choices for themselves and to predict the choices made by GenAI on behalf of a human user. We find that people overestimate the degree of alignment between GenAI'…

Earlier this month, the Copyright Office issued the third part of its report on on AI: this one covering how generative AI may infringe on copyright and whether that's fair use (short answer: maybe, maybe not). I have a new article up summarizing the report.
https://www.…

Copyright Office's report discusses whether generative AI use is fair use
Earlier this month, the Copyright Office issued the third part of its report on AI. As with the first two parts, the Copyright Office discusses arguments from people who responded to its call for comments and then provides its analysis. The three main sections in this part focus on infringement, fair use, and licensing regimes. Here, I’m going to cover what the report says about the first two items: whether using copyrighted material in generative AI infringes on owners’ rights and whether…

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
Shuan Chen, Gunwook Nam, Yousung Jung
https://arxiv.org/abs/2507.02752

Synthesizable by Design: A Retrosynthesis-Guided Framework for Molecular Analog Generation
The disconnect between AI-generated molecules with desirable properties and their synthetic feasibility remains a critical bottleneck in computational drug and material discovery. While generative AI has accelerated the proposal of candidate molecules, many of these structures prove challenging or impossible to synthesize using established chemical reactions. Here, we introduce SynTwins, a novel retrosynthesis-guided molecular analog design framework that designs synthetically accessible molecu…

Securing AI Systems: A Guide to Known Attacks and Impacts
Naoto Kiribuchi, Kengo Zenitani, Takayuki Semitsu
https://arxiv.org/abs/2506.23296 https://

Securing AI Systems: A Guide to Known Attacks and Impacts
Embedded into information systems, artificial intelligence (AI) faces security threats that exploit AI-specific vulnerabilities. This paper provides an accessible overview of adversarial attacks unique to predictive and generative AI systems. We identify eleven major attack types and explicitly link attack techniques to their impacts -- including information leakage, system compromise, and resource exhaustion -- mapped to the confidentiality, integrity, and availability (CIA) security triad. We…

Semantics-Guided Generative Image Compression
Cheng-Lin Wu, Hyomin Choi, Ivan V. Baji\'c
https://arxiv.org/abs/2505.24015 https://

Semantics-Guided Generative Image Compression
Advancements in text-to-image generative AI with large multimodal models are spreading into the field of image compression, creating high-quality representation of images at extremely low bit rates. This work introduces novel components to the existing multimodal image semantic compression (MISC) approach, enhancing the quality of the generated images in terms of PSNR and perceptual metrics. The new components include semantic segmentation guidance for the generative decoder, as well as content…

This https://arxiv.org/abs/2506.00202 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & know…

Frontiers of Generative AI for Network Optimization: Theories, Limits, and Visions
Bo Yang, Ruihuai Liang, Weixin Li, Han Wang, Xuelin Cao, Zhiwen Yu, Samson Lasaulce, M\'erouane Debbah, Mohamed-Slim Alouini, H. Vincent Poor, Chau Yuen
https://arxiv.org/abs/2507.01773

Frontiers of Generative AI for Network Optimization: Theories, Limits, and Visions
While interest in the application of generative AI (GenAI) in network optimization has surged in recent years, its rapid progress has often overshadowed critical limitations intrinsic to generative models that remain insufficiently examined in existing literature. This survey provides a comprehensive review and critical analysis of GenAI in network optimization. We focus on the two dominant paradigms of GenAI including generative diffusion models (GDMs) and large pre-trained models (LPTMs), and…

Has anyone considered or encountered a "Generative AI usage statement" in a manuscript before? I'm thinking of adding one to make clear what genAI was/wasn't used to do in an upcoming submission.

There's some discourse on generative AI "democratizing" art.
And this is so confusing to me. I create images. And when I do, I'm trying to take something in my head, and make it real. And share that image in my head with others.
It's my image in my head. If I describe that to AI to make the image, then it is just approximate. To get it closer to my image needs a better prompt.
That's writing. Writing it its own art, and you can let the reader imagi…

This https://arxiv.org/abs/2505.23405 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A Practical Guide for Supporting Formative Assessment and Feedback Using Generative AI
Formative assessment is a cornerstone of effective teaching and learning, providing students with feedback to guide their learning. While there has been an exponential growth in the application of generative AI in scaling various aspects of formative assessment, ranging from automatic question generation to intelligent tutoring systems and personalized feedback, few have directly addressed the core pedagogical principles of formative assessment. Here, we critically examined how generative AI, e…

Computer science programs at Carnegie Mellon and other US universities are rethinking how to incorporate AI into curricula, including a focus on AI literacy (Steve Lohr/New York Times)
https://www.nytimes.com/2025/06/30/technology/computer-science-…

How Do You Teach Computer Science in the A.I. Era?
Universities across the country are scrambling to understand the implications of generative A.I.’s transformation of technology.

This https://arxiv.org/abs/2505.22073 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents
Due to its general-purpose nature, Generative AI is applied in an ever-growing set of domains and tasks, leading to an expanding set of risks of harm impacting people, communities, society, and the environment. These risks may arise due to failures during the design and development of the technology, as well as during its release, deployment, or downstream usages and appropriations of its outputs. In this paper, building on prior taxonomies of AI risks, harms, and failures, we construct a taxon…

Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
https://arxiv.org/abs/2506.22884

Performance Measurements in the AI-Centric Computing Continuum Systems
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud, edge, Internet of Things (IoT), and mobile platforms work together to support a wide range of applications. Recently, the emergence of Generative AI and large language models has further intensified the demand for computational resources across this continuum…

Two cartoonists, Joe Dworetzky at Bay City News and Pulitzer-winner Mark Fiore, describe how generative AI tools can assist in, not replace, their work (Andrew Deck/Nieman Lab)
https://www.niemanlab.org/2025/06/i-dont-w

AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma
Megan T. deBettencourt, Sruthi Sakthivel, Emily A. Holmes, Mark Chevillet
https://arxiv.org/abs/2507.01081

AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma
Trauma prevalence is vast globally. Evidence-based digital treatments can help, but most require human guidance. Human guides provide tailored instructions and responsiveness to internal cognitive states, but limit scalability. Can generative AI and neurotechnology provide a scalable alternative? Here we test ANTIDOTE, combining AI guidance and pupillometry to automatically deliver and monitor an evidence-based digital treatment, specifically the Imagery Competing Task Intervention (ICTI), to r…

SD-Acc: Accelerating Stable Diffusion through Phase-aware Sampling and Hardware Co-Optimizations
Zhican Wang, Guanghui He, Hongxiang Fan
https://arxiv.org/abs/2507.01309

SD-Acc: Accelerating Stable Diffusion through Phase-aware Sampling and Hardware Co-Optimizations
The emergence of diffusion models has significantly advanced generative AI, improving the quality, realism, and creativity of image and video generation. Among them, Stable Diffusion (StableDiff) stands out as a key model for text-to-image generation and a foundation for next-generation multi-modal algorithms. However, its high computational and memory demands hinder inference speed and energy efficiency. To address these challenges, we identify three core issues: (1) intensive and often redund…

At my keynote for the 2025 Acadia Ethics Conference, a number of clinical therapists in attendance surprised me by embracing AI's potential to bridge mental health gaps and even flag anxiety-producing items in their offices from a single photo.
https://www.

May 2025 recap | The latest edition of the GÉANT School of Software Engineering, hosted by PCSS, brought together developers and experts from across Europe to explore generative #AI tools, risks, secure coding practices.
Highlights:
🔹#GenAI Buzz-Free Programming with LLMs – training by Maciej Łabędzki…

Responsible AI in Practice: Shaping a Safer Future for AI-Powered Software Development | GÉANT CONNECT Online
Poznań, 20–22 May 2025 — The latest edition of the GÉANT School of Software Engineering, held at the Poznań Supercomputing and Networking Center (PSNC), brought together top-tier developers and experts from across Europe for a deep-dive into generative AI tools, risks, and secure coding practices. At the core of the event was the acclaimed training

"You can tell what happened — Google promised iNaturalist free money if they would just do something, anything, that had some generative AI in it. iNaturalist forgot why people contribute at all, and took the cash."
(Original title: Google bribes iNaturalist to use generative AI — volunteers quit in outrage)

Google bribes iNaturalist to use generative AI — volunteers quit in outrage
iNaturalist is a website that crowdsources pictures of plants and animals to help identify species. Its tagline is “A Community for Naturalists.” iNaturalist is administered by its own small charit…

University of Chicago Becker-Friedman Institute of Economics just published research this April 2025 of how Generative AI has had "almost no significant wage or labor impact so far".
✅ Large Language Models, Small Labor Market Effects
https://papers.ssrn.com/sol3/papers.cf

Watermarking Without Standards Is Not AI Governance
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
https://arxiv.org/abs/2505.23814 https://

Watermarking Without Standards Is Not AI Governance
Watermarking has emerged as a leading technical proposal for attributing generative AI content and is increasingly cited in global governance frameworks. This paper argues that current implementations risk serving as symbolic compliance rather than delivering effective oversight. We identify a growing gap between regulatory expectations and the technical limitations of existing watermarking schemes. Through analysis of policy proposals and industry practices, we show how incentive structures di…

In its December 2023 lawsuit against OpenAI, The New York Times produced dozens of examples where GPT-4 exactly reproduced significant passages from Times stories.
In its response, OpenAI described this as a “fringe behavior” and a “problem that researchers at OpenAI and elsewhere work hard to address.”
But is it actually a fringe behavior?
And have leading AI companies addressed it? 
New research—focusing on books rather than newspaper articles and on different compa…

Study: Meta AI model can reproduce almost half of Harry Potter book
The research could have big implications for generative AI copyright lawsuits.

This https://arxiv.org/abs/2411.10877 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development
Despite the utility that Generative AI (GenAI) tools provide for tasks such as writing code, the use of these tools raises important legal questions and potential risks, particularly those associated with copyright law. As lawmakers and regulators engage with those questions, the views of users can provide relevant perspectives. In this paper, we provide: (1) a survey of 574 developers on the licensing and copyright aspects of GenAI for coding, as well as follow-up interviews; (2) a snapshot of…

TAG-WM: Tamper-Aware Generative Image Watermarking via Diffusion Inversion Sensitivity
Yuzhuo Chen, Zehua Ma, Han Fang, Weiming Zhang, Nenghai Yu
https://arxiv.org/abs/2506.23484 …

TAG-WM: Tamper-Aware Generative Image Watermarking via Diffusion Inversion Sensitivity
AI-generated content (AIGC) enables efficient visual creation but raises copyright and authenticity risks. As a common technique for integrity verification and source tracing, digital image watermarking is regarded as a potential solution to above issues. Among these, watermarking methods capable of preserving the generation quality are receiving increased attention. However, the proliferation and high performance of generative image editing applications have elevated the risks of malicious tam…

In einem eventuellen Streit zwischen Meta und J. K. Rowling kann sich keine Seite auf mich verlassen. (Und sie brauchen mich ja auch gar nicht.)
https://arstechnica.com/ai/2025/06/study-metas-llama-3-1-can-recall-42-percent-of-the…

Study: Meta AI model can reproduce almost half of Harry Potter book
The research could have big implications for generative AI copyright lawsuits.

«Sometimes a charity where volunteers do all the work forgets who does all the work and that these are volunteers, not minions. If someone waves a bit of money at them.»
https://pivot-to-ai.com/2025/06/19/google-bribes-inaturalist-to-use-generative-ai-volunteers-quit-in-outrage/

AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models
Anthony M. Barrett, Jessica Newman, Brandie Nonnecke, Nada Madkour, Dan Hendrycks, Evan R. Murphy, Krystal Jackson, Deepika Raman
https://arxiv.org/abs/2506.23949

AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models
Increasingly multi-purpose AI models, such as cutting-edge large language models or other 'general-purpose AI' (GPAI) models, 'foundation models,' generative AI models, and 'frontier models' (typically all referred to hereafter with the umbrella term 'GPAI/foundation models' except where greater specificity is needed), can provide many beneficial capabilities but also risks of adverse events with profound consequences. This document provides risk-management practices or controls for identifying…

Rethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Agentic Group Decision Support
Dietmar Jannach, Amra Deli\'c, Francesco Ricci, Markus Zanker
https://arxiv.org/abs/2507.00535

Rethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Agentic Group Decision Support
More than twenty-five years ago, first ideas were developed on how to design a system that can provide recommendations to groups of users instead of individual users. Since then, a rich variety of algorithmic proposals were published, e.g., on how to acquire individual preferences, how to aggregate them, and how to generate recommendations for groups of users. However, despite the rich literature on the topic, barely any examples of real-world group recommender systems can be found. This lets u…

Generative AI and Organizational Structure in the Knowledge Economy
Fasheng Xu, Jing Hou, Wei Chen, Karen Xie
https://arxiv.org/abs/2506.00532 https://

Generative AI and Organizational Structure in the Knowledge Economy
The adoption of GenAI is fundamentally reshaping organizations in the knowledge economy. GenAI can significantly enhance workers' problem-solving abilities and productivity, yet it also presents a major reliability challenge: hallucinations, or errors presented as plausible outputs. This study develops a theoretical model to examine GenAI's impact on organizational structure and the role of human-in-the-loop oversight. Our findings indicate that successful GenAI adoption hinges primarily on mai…

AI's real threat to education isn't that it encourages students to cheat, but that it short-circuits the learning processes needed to use generative AI adeptly (Nicholas Carr/New Cartographies)
https://www.newcartographies.com/p/the-myth-of-automated-lear…

The Myth of Automated Learning
AI's real threat to education.

Enhancing Critical Thinking in Generative AI Search with Metacognitive Prompts
Anjali Singh, Zhitong Guan, Soo Young Rieh
https://arxiv.org/abs/2505.24014 …

Enhancing Critical Thinking in Generative AI Search with Metacognitive Prompts
The growing use of Generative AI (GenAI) conversational search tools has raised concerns about their effects on people's metacognitive engagement, critical thinking, and learning. As people increasingly rely on GenAI to perform tasks such as analyzing and applying information, they may become less actively engaged in thinking and learning. This study examines whether metacognitive prompts - designed to encourage people to pause, reflect, assess their understanding, and consider multiple perspec…

Can AI be Consentful?
Giada Pistilli, Bruna Trevelin
https://arxiv.org/abs/2507.01051 https://arxiv.org/pdf/2507.01051

Can AI be Consentful?
The evolution of generative AI systems exposes the challenges of traditional legal and ethical frameworks built around consent. This chapter examines how the conventional notion of consent, while fundamental to data protection and privacy rights, proves insufficient in addressing the implications of AI-generated content derived from personal data. Through legal and ethical analysis, we show that while individuals can consent to the initial use of their data for AI training, they cannot meaningf…

What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Matthew Kam, Cody Miller, Miaoxin Wang, Abey Tidwell, Irene A. Lee, Joyce Malyn-Smith, Beatriz Perez, Vikram Tiwari, Joshua Kenitzer, Andrew Macvean, Erin Barrar
https://arxiv.org/abs/2506.00202…

What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & know…

Using Generative AI in Software Design Education: An Experience Report
Victoria Jackson, Susannah Liu, Andre van der Hoek
https://arxiv.org/abs/2506.21703 …

Using Generative AI in Software Design Education: An Experience Report
With the rapid adoption of Generative AI (GenAI) tools, software engineering educators have grappled with how best to incorporate them into the classroom. While some research discusses the use of GenAI in the context of learning to code, there is little research that explores the use of GenAI in the classroom for other areas of software development. This paper provides an experience report on introducing GenAI into an undergraduate software design class. Students were required to use GenAI (in …

Visual Privacy Management with Generative AI for Blind and Low-Vision People
Tanusree Sharma, Yu-Yun Tseng, Lotus Zhang, Ayae Ide, Kelly Avery Mack, Leah Findlater, Danna Gurari, Yang Wang
https://arxiv.org/abs/2507.00286

Visual Privacy Management with Generative AI for Blind and Low-Vision People
Blind and low vision (BLV) individuals use Generative AI (GenAI) tools to interpret and manage visual content in their daily lives. While such tools can enhance the accessibility of visual content and so enable greater user independence, they also introduce complex challenges around visual privacy. In this paper, we investigate the current practices and future design preferences of blind and low vision individuals through an interview study with 21 participants. Our findings reveal a range of c…

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review
Seyma Yaman Kayadibi
https://arxiv.org/abs/2507.01062

Quantifying Student Success with Generative AI: A Monte Carlo Simulation Informed by Systematic Review
The exponential development of generative artificial intelligence (GenAI) technologies like ChatGPT has raised increasing curiosity about their use in higher education, specifically with respect to how students view them, make use of them, and the implications for learning outcomes. This paper employs a hybrid methodological approach involving a systematic literature review and simulation-based modeling to explore student perceptions of GenAI use in the context of higher education. A total of n…

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
Huiwen Han
https://arxiv.org/abs/2506.22477

Innovative Research on IoT Architecture and Robotic Operating Platforms: Applications of Large Language Models and Generative AI
This paper introduces an innovative design for robotic operating platforms, underpinned by a transformative Internet of Things (IoT) architecture, seamlessly integrating cutting-edge technologies such as large language models (LLMs), generative AI, edge computing, and 5G networks. The proposed platform aims to elevate the intelligence and autonomy of IoT systems and robotics, enabling them to make real-time decisions and adapt dynamically to changing environments. Through a series of compelling…

This https://arxiv.org/abs/2405.02696 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model
Latent Diffusion Models (LDMs) enable a wide range of applications but raise ethical concerns regarding illegal utilization. Adding watermarks to generative model outputs is a vital technique employed for copyright tracking and mitigating potential risks associated with Artificial Intelligence (AI)-generated contents. However, post-processed watermarking methods are unable to withstand generative watermark attacks and there exists a trade-off between image fidelity and watermark strength. There…

A US judge rules that Meta's use of books to train AI is protected by fair use but says his opinion is more a reflection of the plaintiffs' poor arguments (Isaiah Poritz/Bloomberg Law)
https://news.bloomberglaw.com/legal-op

Meta Beats Copyright Suit From Authors Over AI Training on Books
Meta Platforms Inc. escaped a first-of-its-kind copyright lawsuit from a group of authors who alleged the tech giant hoovered up millions of copyrighted books without permission to train its generative AI model called Llama.

A US judge rules that Meta's use of books to train AI is protected by fair use but says his opinion is more a reflection of the plaintiffs' poor arguments (Isaiah Poritz/Bloomberg Law)
https://news.bloomberglaw.com/legal-op

Meta Beats Authors’ Copyright Suit Over AI Training on Books (2)
Meta Platforms Inc. escaped a first-of-its-kind copyright lawsuit from a group of authors who alleged the tech giant hoovered up millions of copyrighted books without permission to train its generative AI model called Llama.

Generative Knowledge Production Pipeline Driven by Academic Influencers
Katalin Feher, Marton Demeter
https://arxiv.org/abs/2505.24681 https://

Generative Knowledge Production Pipeline Driven by Academic Influencers
Generative AI transforms knowledge production, validation, and dissemination, raising academic integrity and credibility concerns. This study examines 53 academic influencer videos that reached 5.3 million viewers to identify an emerging, structured, implementation-ready pipeline balancing originality, ethical compliance, and human-AI collaboration despite the disruptive impacts. Findings highlight generative AI's potential to automate publication workflows and democratize participation in know…

Encouraging Students' Responsible Use of GenAI in Software Engineering Education: A Causal Model and Two Institutional Applications
Vahid Garousi, Zafar Jafarov, Aytan Movsumova, Atif Namazov, Huseyn Mirzayev
https://arxiv.org/abs/2506.00682

Encouraging Students' Responsible Use of GenAI in Software Engineering Education: A Causal Model and Two Institutional Applications
Context: As generative AI (GenAI) tools such as ChatGPT and GitHub Copilot become pervasive in education, concerns are rising about students using them to complete rather than learn from coursework-risking overreliance, reduced critical thinking, and long-term skill deficits. Objective: This paper proposes and empirically applies a causal model to help educators scaffold responsible GenAI use in Software Engineering (SE) education. The model identifies how professor actions, student factors, …

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects
Zihan Hong, Yushi Wu, Zhiting Zhao, Shanshan Feng, Jianghong Ma, Jiao Liu, Tianjun Wei
https://arxiv.org/abs/2506.16893

Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects
With the recent progress in generative artificial intelligence (Generative AI), particularly in the development of large language models, recommendation systems are evolving to become more versatile. Unlike traditional techniques, generative AI not only learns patterns and representations from complex data but also enables content generation, data synthesis, and personalized experiences. This generative capability plays a crucial role in the field of recommendation systems, helping to address t…

Daydream, which raised a $50M seed in June 2024 to build a generative AI shopping agent for fashion, launches in beta, with an app expected later this summer (Hilary Milnes/Vogue Business)
https://www.voguebusiness.com/story/techno

Is Daydream’s AI platform the answer to fashion’s discovery problem?
Founder Julie Bornstein raised $50 million last year to create the ultimate AI shopping experience. Today, it launches in beta.

AnyAni: An Interactive System with Generative AI for Animation Effect Creation and Code Understanding in Web Development
Tianrun Qiu, Yuxin Ma
https://arxiv.org/abs/2506.21962

AnyAni: An Interactive System with Generative AI for Animation Effect Creation and Code Understanding in Web Development
Generative AI assistants have been widely used in front-end programming. However, besides code writing, developers often encounter the need to generate animation effects. As novices in creative design without the assistance of professional designers, developers typically face difficulties in describing, designing, and implementing desired animations. To address this issue, we conducted a formative study (N=6) to identify the challenges that code developers face when dealing with animation desig…

Generative AI-enhanced Low-Altitude UAV-Mounted Stacked Intelligent Metasurfaces
Geng Sun, Mingzhe Fan, Lei Zhang, Hongyang Pan, Jiahui Li, Chuang Zhang, Linyao Li, Changyuan Zhao, Chau Yuen
https://arxiv.org/abs/2506.23488

Generative AI-enhanced Low-Altitude UAV-Mounted Stacked Intelligent Metasurfaces
Wireless communication systems face significant challenges in meeting the increasing demands for higher data rates and more reliable connectivity in complex environments. Stacked intelligent metasurfaces (SIMs) have emerged as a promising technology for realizing wave-domain signal processing, with mobile SIMs offering superior communication performance compared to their fixed counterparts. In this paper, we investigate a novel unmanned aerial vehicle (UAV)-mounted SIMs (UAV-SIMs) assisted comm…

GATSim: Urban Mobility Simulation with Generative Agents
Qi Liu, Can Li, Wanjing Ma
https://arxiv.org/abs/2506.23306 https://arxiv.or…

GATSim: Urban Mobility Simulation with Generative Agents
Traditional agent-based urban mobility simulations rely on rigid rule-based systems that fail to capture the complexity, adaptability, and behavioral diversity characteristic of human travel decision-making. Recent advances in large language models and AI agent technology offer opportunities to create agents with reasoning capabilities, persistent memory, and adaptive learning mechanisms. We propose GATSim (Generative-Agent Transport Simulation), a novel framework that leverages these advances …

Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center
James Wen, Sahil Nalawade, Zhiwei Liang, Catherine Bielick, Marisa Ferrara Boston, Alexander Chowdhury, Adele Collin, Luigi De Angelis, Jacob Ellen, Heather Frase, Rodrigo R. Gameiro, Juan Manuel Gutierrez, Pooja Kadam, Murat Keceli, Srikanth Krishnamurthy, Anne Kwok, Yanan Lance Lu, Heather Mattie, Liam G. McCoy, Katherine Miller, Allison C. Morgan, Marlene Louisa Moerig, Tran…

Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center
Generative AI is present in multiple industries. Dana-Farber Cancer Institute, in partnership with Microsoft, has created an internal AI tool, GPT4DFCI. Together we hosted a red teaming event to assess whether the underlying GPT models that support the tool would output copyrighted data. Our teams focused on reproducing content from books, news articles, scientific articles, and electronic health records. We found isolated instances where GPT4DFCI was able to identify copyrighted material and r…

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
Russell Beale
https://arxiv.org/abs/2506.22231

Adapting University Policies for Generative AI: Opportunities, Challenges, and Policy Solutions in Higher Education
The rapid proliferation of generative artificial intelligence (AI) tools - especially large language models (LLMs) such as ChatGPT - has ushered in a transformative era in higher education. Universities in developed regions are increasingly integrating these technologies into research, teaching, and assessment. On one hand, LLMs can enhance productivity by streamlining literature reviews, facilitating idea generation, assisting with coding and data analysis, and even supporting grant proposal d…

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
Shuo Yang, Xinran Zheng, Jinfeng Xu, Jinze Li, Danyang Song, Zheyu Chen, Edith C. H. Ngai
https://arxiv.org/abs/2506.20488

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
The rapid advancement of 6G wireless networks, IoT, and edge computing has significantly expanded the cyberattack surface, necessitating more intelligent and adaptive vulnerability detection mechanisms. Traditional security methods, while foundational, struggle with zero-day exploits, adversarial threats, and context-dependent vulnerabilities in highly dynamic network environments. Generative AI (GAI) emerges as a transformative solution, leveraging synthetic data generation, multimodal reasoni…

Integrating Universal Generative AI Platforms in Educational Labs to Foster Critical Thinking and Digital Literacy
Vasiliy Znamenskiy, Rafael Niyazov, Joel Hernandez
https://arxiv.org/abs/2507.00007

Integrating Universal Generative AI Platforms in Educational Labs to Foster Critical Thinking and Digital Literacy
This paper presents a new educational framework for integrating generative artificial intelligence (GenAI) platforms such as ChatGPT, Claude, and Gemini into laboratory activities aimed at developing critical thinking and digital literacy among undergraduate students. Recognizing the limitations and risks of uncritical reliance on large language models (LLMs), the proposed pedagogical model reframes GenAI as a research subject and cognitive tool. Students formulate discipline-specific prompts a…

Amazon's VP of Generative AI Vasi Philomin left for another company; VP of Amazon Elastic Block Store Rajesh Sheth assumed some of Philomin's responsibilities (Greg Bensinger/Reuters)
https://www.reuters.com/business/retail-co…

Software Reuse in the Generative AI Era: From Cargo Cult Towards AI Native Software Engineering
Tommi Mikkonen, Antero Taivalsaari
https://arxiv.org/abs/2506.17937

Software Reuse in the Generative AI Era: From Cargo Cult Towards AI Native Software Engineering
Software development is currently under a paradigm shift in which artificial intelligence and generative software reuse are taking the center stage in software creation. Consequently, earlier software reuse practices and methods are rapidly being replaced by AI-assisted approaches in which developers place their trust on code that has been generated by artificial intelligence. This is leading to a new form of software reuse that is conceptually not all that different from cargo cult development…

Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
Clemente Rubio-Manzano, Jazna Meza, Rodolfo Fernandez-Santibanez, Christian Vidal-Castro
https://arxiv.org/abs/2507.00108

Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
Computer programming is undergoing a true transformation driven by powerful new tools for automatic source code generation based on large language models. This transformation is also manifesting in introductory programming courses at universities around the world, generating an in-depth debate about how programming content should be taught, learned, and assessed in the context of generative artificial intelligence. This article aims, on the one hand, to review the most relevant studies on thi…

Email as the Interface to Generative AI Models: Seamless Administrative Automation
Andres Navarro, Carlos de Quinto, Jos\'e Alberto Hern\'andez
https://arxiv.org/abs/2506.23850

Email as the Interface to Generative AI Models: Seamless Administrative Automation
This paper introduces a novel architectural framework that integrates Large Language Models (LLMs) with email interfaces to automate administrative tasks, specifically targeting accessibility barriers in enterprise environments. The system connects email communication channels with Optical Character Recognition (OCR) and intelligent automation, enabling non-technical administrative staff to delegate complex form-filling and document processing tasks using familiar email interfaces. By treating …

On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
Stanley Wu, Ronik Bhaskar, Anna Yoo Jeong Ha, Shawn Shan, Haitao Zheng, Ben Y. Zhao
https://arxiv.org/abs/2506.21874

On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
Today's text-to-image generative models are trained on millions of images sourced from the Internet, each paired with a detailed caption produced by Vision-Language Models (VLMs). This part of the training pipeline is critical for supplying the models with large volumes of high-quality image-caption pairs during training. However, recent work suggests that VLMs are vulnerable to stealthy adversarial attacks, where adversarial perturbations are added to images to mislead the VLMs into producing …

Internal memo: Goldman Sachs launches a generative AI assistant firmwide to boost productivity; around 10,000 employees are already using the GS AI Assistant (Reuters)
https://www.reuters.com/business/goldman-sachs-launches-ai-a…

Understanding the Challenges and Promises of Developing Generative AI Apps: An Empirical Study
Buthayna AlMulla, Maram Assi, Safwat Hassan
https://arxiv.org/abs/2506.16453

Understanding the Challenges and Promises of Developing Generative AI Apps: An Empirical Study
The release of ChatGPT in 2022 triggered a rapid surge in generative artificial intelligence mobile apps (i.e., Gen-AI apps). Despite widespread adoption, little is known about how end users perceive and evaluate these Gen-AI functionalities in practice. In this work, we conduct a user-centered analysis of 676,066 reviews from 173 Gen-AI apps on the Google Play Store. We introduce a four-phase methodology, SARA (Selection, Acquisition, Refinement, and Analysis), that enables the systematic extr…

A Practical Guide for Supporting Formative Assessment and Feedback Using Generative AI
Sapolnach Prompiengchai, Charith Narreddy, Steve Joordens
https://arxiv.org/abs/2505.23405

A Practical Guide for Supporting Formative Assessment and Feedback Using Generative AI
Formative assessment is a cornerstone of effective teaching and learning, providing students with feedback to guide their learning. While there has been an exponential growth in the application of generative AI in scaling various aspects of formative assessment, ranging from automatic question generation to intelligent tutoring systems and personalized feedback, few have directly addressed the core pedagogical principles of formative assessment. Here, we critically examined how generative AI, e…

Adobe releases iOS and Android apps for Firefly, letting users generate images and videos using text prompts and experiment with popular AI photo editing tools (Jess Weatherbed/The Verge)
https://www.theverge.com/news/688080/adobe-firefly-…

Adobe made a mobile app for its Firefly generative AI tools
The all-in-one platform for Adobe’s Firefly generative AI models is now available on iPhone and Android devices.

This https://arxiv.org/abs/2505.17418 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI
Generative AI (genAI) tools are advertised as productivity aids. Yet, issues related to miscalibrated trust and usage friction continue to hinder their adoption. Additionally, AI can be exclusionary, failing to support diverse users adequately, further exacerbating these concerns. One such aspect of diversity is cognitive diversity -- variations in users' cognitive styles -- that leads to divergence in interaction styles. When an individual's cognitive styles are unsupported, it creates additio…

From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI
Sharique Hasan, Alexander Oettl, Sampsa Samila
https://arxiv.org/abs/2506.22440

From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI
This paper introduces the Generality-Accuracy-Simplicity (GAS) framework to analyze how large language models (LLMs) are reshaping organizations and competitive strategy. We argue that viewing AI as a simple reduction in input costs overlooks two critical dynamics: (a) the inherent trade-offs among generality, accuracy, and simplicity, and (b) the redistribution of complexity across stakeholders. While LLMs appear to defy the traditional trade-off by offering high generality and accuracy throug…

Generative AI enterprise search startup Glean raises a $150M Series F led by Wellington Management, bringing its valuation to $7.2B, up from $4.6B in Sept. 2024 (Afshan Musani/CNBC)
https://www.cnbc.com/2025/06/10/glean-gen-ai…

Glean, gen AI enterprise search startup, raises $150 million in deal adding billions to valuation
Glean, a generative AI enterprise search startup, raised $150 million from investors in a deal that increased its valuation to over $7 billion.

AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System
Lancelot Blanchard, Cameron Holt, Joseph A. Paradiso
https://arxiv.org/abs/2506.18143

AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System
Vocals harmonizers are powerful tools to help solo vocalists enrich their melodies with harmonically supportive voices. These tools exist in various forms, from commercially available pedals and software to custom-built systems, each employing different methods to generate harmonies. Traditional harmonizers often require users to manually specify a key or tonal center, while others allow pitch selection via an external keyboard-both approaches demanding some degree of musical expertise. The AI …

London- and Paris-based Animaj, a kids' media company that uses proprietary generative AI production tools to automate animation pipelines, raised $85M (Elsa Keslassy/Variety)
https://variety.com/2025/digital/global/…

HarbourView Equity Leads $85 Million Investment in Animaj
HarbourView Equity Partners is leading a $85-million investment in Animaj, the AI-powered media company specializing in kids & family entertainment.

Distinguishing Predictive and Generative AI in Regulation
Jennifer Wang, Andrew Selbst, Solon Barocas, Suresh Venkatasubramanian
https://arxiv.org/abs/2506.17347

Distinguishing Predictive and Generative AI in Regulation
Over the past decade, policymakers have developed a set of regulatory tools to ensure AI development aligns with key societal goals. Many of these tools were initially developed in response to concerns with predictive AI and therefore encode certain assumptions about the nature of AI systems and the utility of certain regulatory approaches. With the advent of generative AI, however, some of these assumptions no longer hold, even as policymakers attempt to maintain a single regulatory target tha…

Meta launches generative AI tools in its Advantage suite for advertisers and agencies at Cannes, including to turn still images into videos and Virtual Try-On (Mark Mwachiro/Adweek)
https://www.adweek.com/brand-marketing/meta…

Meta’s Advantage+ Adds Gen AI Tools for Advertisers and Agencies
The new features include the ability to transform still images into video.

Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT
Simon Hatzesberger, Iris Nonneman
https://arxiv.org/abs/2506.18942

Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT
This article demonstrates the transformative impact of Generative AI (GenAI) on actuarial science, illustrated by four implemented case studies. It begins with a historical overview of AI, tracing its evolution from early neural networks to modern GenAI technologies. The first case study shows how Large Language Models (LLMs) improve claims cost prediction by deriving significant features from unstructured textual data, significantly reducing prediction errors in the underlying machine learning…