Tootfinder

Massive extended streamers feed high-mass young stars
Fernando A. Olguin, Patricio Sanhueza, Adam Ginsburg, Huei-Ru Vivien Chen, Kei E. I. Tanaka, Xing Lu, Kaho Morii, Fumitaka Nakamura, Shanghuo Li, Yu Cheng, Qizhou Zhang, Qiuyi Luo, Yoko Oya, Takeshi Sakai, Masao Saito, Andr\'es E. Guzm\'an
https://arxiv.org/abs/2508.15889…

Massive extended streamers feed high-mass young stars
Stars are born in a variety of environments that determine how they gather gas to achieve their final masses. It is generally believed that disks are ubiquitous around protostars as a result of angular momentum conservation and are natural places to grow planets. As such, they are proposed to be the last link in the inflow chain from the molecular cloud to the star. However, disks are not the only form that inflows can take. Here we report on high-resolution observations performed with the Atac…

"In a broader sense, however, today’s ruling is of a piece with this Court’s recent tendencies. “[R]ight when the Judiciary should be hunkering down to do all it can to preserve the law’s constraints,” the Court opts instead to make vindicating the rule of law and preventing manifestly injurious Government action as difficult as possible….. This is Calvinball jurisprudence with a twist. Calvinball has only one rule: There are no fixed rules. We seem to have two: that one, and this Admin…

Justice Jackson Correctly Defines The John Roberts Supreme Court As The Calvinball Court
In theory, the nice thing about having a Supreme Court is that it provides some level of legal certainty. You know how the system works: lower courts make decisions based on law and precedent, part…

GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design
Wen-Fan Wang, Ting-Ying Lee, Chien-Ting Lu, Che-Wei Hsu, Nil Ponsa Campany, Yu Chen, Mike Y. Chen, Bing-Yu Chen
https://arxiv.org/abs/2508.15227

GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design
Environment designers in the entertainment industry create imaginative 2D and 3D scenes for games, films, and television, requiring both fine-grained control of specific details and consistent global coherence. Designers have increasingly integrated generative AI into their workflows, often relying on large language models (LLMs) to expand user prompts for text-to-image generation, then iteratively refining those prompts and applying inpainting. However, our formative study with 10 designers su…

Thyme: Think Beyond Images
Yi-Fan Zhang, Xingyu Lu, Shukang Yin, Chaoyou Fu, Wei Chen, Xiao Hu, Bin Wen, Kaiyu Jiang, Changyi Liu, Tianke Zhang, Haonan Fan, Kaibing Chen, Jiankang Chen, Haojie Ding, Kaiyu Tang, Zhang Zhang, Liang Wang, Fan Yang, Tingting Gao, Guorui Zhou
https://arxiv.org/abs/2508.11630

Thyme: Think Beyond Images
Following OpenAI's introduction of the ``thinking with images'' concept, recent efforts have explored stimulating the use of visual information in the reasoning process to enhance model performance in perception and reasoning tasks. However, to the best of our knowledge, no open-source work currently offers a feature set as rich as proprietary models (O3), which can perform diverse image manipulations and simultaneously enhance logical reasoning capabilities through code. In this paper, we make…

How popular media gets love wrong
Now a bit of background about why I have this "engineered" model of love:
First, I'm a white straight cis man. I've got a few traits that might work against my relationship chances (e.g., neurodivergence; I generally fit pretty well into the "weird geek" stereotype), but as I was recently reminded, it's possible my experience derives more from luck than other factors, and since things are tilted more in my favor than most people on the planet, my advice could be worse than useless if it leads people towards strategies that would only have worked for someone like me. I don't *think* that's the case, but it's worth mentioning explicitly.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
I'm lucky in that I had some mixed-gender social circles already like intramural soccer and a graduate-student housing potluck. Graduate school makes a *lot* more of these social spaces accessible, so I recognize that those not in school of some sort have a harder time of things, especially if like me they don't feel like they fit in in typical adult social spaces like bars.
However, at one point I just decided that my desire for a relationship would need action on my part and so I'd try to build a relationship and see what happened. I worked up my courage and asked one of the people in my potluck if she'd like to go for a hike (pretty much clearly a date but not explicitly one; in retrospect not the best first-date modality in a lot of ways, but it made a little more sense in our setting where we could go for a hike from our front door). To emphasize this point: I was not in love with (or even infatuated with) my now-wife at that point. I made a decision to be open to building a relationship, but didn't follow the typical romance story formula beyond that. Now of course, in real life as opposed to popular media, this isn't anything special. People ask each other out all the time just because they're lonely, and some of those relationships turn out fine (although many do not).
I was lucky in that some aspects of who I am and what I do happened to be naturally comforting to my wife (natural advantage in the "appeal" model of love) but of course there are some aspects of me that annoy my wife, and we negotiate that. In the other direction, there's some things I instantly liked about my wife, and other things that still annoy me. We've figured out how to accept a little, change a little, and overall be happy with each other (though we do still have arguments; it's not like the operation/construction/maintenance of the "love mechanism" is always perfectly smooth). In particular though, I approached the relationship with the attitude of "I want to try to build a relationship with this person," at first just because of my own desires for *any* relationship, and then gradually more and more through my desire to build *this specific* relationship as I enjoyed the rewards of companionship.
So for example, while I think my wife is objectively beautiful, she's also *subjectively* very beautiful *to me* because having decided to build a relationship with her, I actively tried to see her as beautiful, rather than trying to judge whether I wanted a relationship with her based on her beauty. In other words, our relationship is more causative of her beauty-to-me than her beauty-to-me is causative of our relationship. This is the biggest way I think the "engineered" model of love differs from the "fire" and "appeal" models: you can just decide to build love independent of factors we typically think of as engendering love (NOT independent of your partner's willingness to participate, of course), and then all of those things like "thinking your partner is beautiful" can be a result of the relationship you're building. For sure those factors might affect who is willing to try building a relationship with you in the first place, but if more people were willing to jump into relationship building (not necessarily with full commitment from the start) without worrying about those other factors, they might find that those factors can come out of the relationship instead of being prerequisites for it. I think this is the biggest failure of the "appeal" model in particular: yes you *do* need to do things that appeal to your partner, but it's not just "make myself lovable" it's also: is your partner putting in the effort to see the ways that you are beautiful/lovable/etc., or are they just expecting you to become exactly some perfect person they've imagined (and/or been told to desire by society)? The former is perfectly possible, and no less satisfying than the latter.
To cut off my rambling a bit here, I'll just add that in our progress from dating through marriage through staying-married, my wife and I have both talked at times explicitly about commitment, and especially when deciding to get married, I told her that I knew I couldn't live up to the perfect model of a husband that I'd want to be, but that if she wanted to deepen our commitment, I was happy to do that, and so we did. I also rearranged my priorities at that point, deciding that I knew I wanted to prioritize this relationship above things like my career or my research interests, and while I've not always been perfect at that in my little decisions, I've been good at holding to that in my big decisions at least. In the end, *once we had built a somewhat-committed relationship*, we had something that we both recognized was worth more than most other things in life, and that let us commit even more, thus getting even more out of it in the long term. Obviously you can't start the first date with an expectation of life-long commitment, and you need to synchronize your increasing commitment to a relationship so that it doesn't become lopsided, which is hard. But if you take the commitment as an active decision and as the *precursor* to things like infatuation, attraction, etc., you can build up to something that's incredibly strong and rewarding.
I'll follow this up with one more post trying to distill some advice from my ramblings.
#relationships #love

Generative AI alone may not be enough: Evaluating AI Support for Learning Mathematical Proof
Eason Chen, Sophia Judicke, Kayla Beigh, Xinyi Tang, Zimo Xiao, Chuangji Li, Shizhuo Li, Reed Luttmer, Shreya Singh, Maria Yampolsky, Naman Parikh, Yi Zhao, Meiyi Chen, Scarlett Huang, Anishka Mohanty, Gregory Johnson, John Mackey, Jionghao Lin, Ken Koedinger
https://…

Generative AI alone may not be enough: Evaluating AI Support for Learning Mathematical Proof
We evaluate the effectiveness of LLM-Tutor, a large language model (LLM)-powered tutoring system that combines an AI-based proof-review tutor for real-time feedback on proof-writing and a chatbot for mathematics-related queries. Our experiment, involving 148 students, demonstrated that the use of LLM-Tutor significantly improved homework performance compared to a control group without access to the system. However, its impact on exam performance and time spent on tasks was found to be insignifi…

Inspection Planning Primitives with Implicit Models
Jingyang You, Hanna Kurniawati, Lashika Medagoda
https://arxiv.org/abs/2510.07611 https://arxiv.org/pdf…

Inspection Planning Primitives with Implicit Models
The aging and increasing complexity of infrastructures make efficient inspection planning more critical in ensuring safety. Thanks to sampling-based motion planning, many inspection planners are fast. However, they often require huge memory. This is particularly true when the structure under inspection is large and complex, consisting of many struts and pillars of various geometry and sizes. Such structures can be represented efficiently using implicit models, such as neural Signed Distance Fun…

In-plane polar domains enhanced energy storage
Yu Lei, Xiaoming Shi, Sihan Yan, Qinghua Zhang, Jiecheng Liu, Sixu Wang, Yu Chen, Jiaou Wang, He Qi, Qian Li, Ting Lin, Jingfen Li, Qing Zhu, Haoyu Wang, Jing Chen, Lincong Shu, Linkun Wang, Han Wu, Xianran Xing
https://arxiv.org/abs/2510.11126

In-plane polar domains enhanced energy storage
Relaxor ferroelectric thin films are recognized for their ultrahigh power density, rendering them highly promising for energy storage applications in electrical and electronic systems. However, achieving high energy storage performance with chemically homogeneous, environmentally friendly and compositionally stable materials remains challenging. In this work, we present a design of dielectrics with high energy storage performance via an in-plane polar domains incorporating polar nanoregions mec…

Just read this post by @… on an optimistic AGI future, and while it had some interesting and worthwhile ideas, it's also in my opinion dangerously misguided, and plays into the current AGI hype in a harmful way.
https://social.coop/@eloquence/114940607434005478
My criticisms include:
- Current LLM technology has many layers, but the biggest most capable models are all tied to corporate datacenters and require inordinate amounts of every and water use to run. Trying to use these tools to bring about a post-scarcity economy will burn up the planet. We urgently need more-capable but also vastly more efficient AI technologies if we want to use AI for a post-scarcity economy, and we are *not* nearly on the verge of this despite what the big companies pushing LLMs want us to think.
- I can see that permacommons.org claims a small level of expenses on AI equates to low climate impact. However, given current deep subsidies on place by the big companies to attract users, that isn't a great assumption. The fact that their FAQ dodges the question about which AI systems they use isn't a great look.
- These systems are not free in the same way that Wikipedia or open-source software is. To run your own model you need a data harvesting & cleaning operation that costs millions of dollars minimum, and then you need millions of dollars worth of storage & compute to train & host the models. Right now, big corporations are trying to compete for market share by heavily subsidizing these things, but it you go along with that, you become dependent on them, and you'll be screwed when they jack up the price to a profitable level later. I'd love to see open dataset initiatives SBD the like, and there are some of these things, but not enough yet, and many of the initiatives focus on one problem while ignoring others (fine for research but not the basis for a society yet).
- Between the environmental impacts, the horrible labor conditions and undercompensation of data workers who filter the big datasets, and the impacts of both AI scrapers and AI commons pollution, the developers of the most popular & effective LLMs have a lot of answer for. This project only really mentions environmental impacts, which makes me think that they're not serious about ethics, which in turn makes me distrustful of the whole enterprise.
- Their language also ends up encouraging AI use broadly while totally ignoring several entire classes of harm, so they're effectively contributing to AI hype, especially with such casual talk of AGI and robotics as if embodied AGI were just around the corner. To be clear about this point: we are several breakthroughs away from AGI under the most optimistic assumptions, and giving the impression that those will happen soon plays directly into the hands of the Sam Altmans of the world who are trying to make money off the impression of impending huge advances in AI capabilities. Adding to the AI hype is irresponsible.
- I've got a more philosophical criticism that I'll post about separately.
I do think that the idea of using AI & other software tools, possibly along with robotics and funded by many local cooperatives, in order to make businesses obsolete before they can do the same to all workers, is a good one. Get your local library to buy a knitting machine alongside their 3D printer.
Lately I've felt too busy criticizing AI to really sit down and think about what I do want the future to look like, even though I'm a big proponent of positive visions for the future as a force multiplier for criticism, and this article is inspiring to me in that regard, even if the specific project doesn't seem like a good one.

How popular media gets love wrong
Had some thoughts in response to a post about loneliness on here. As the author emphasized, reassurances from people who got lucky are not terribly comforting to those who didn't, especially when the person who was lucky had structural factors in their favor that made their chances of success much higher than those is their audience. So: these are just my thoughts, and may not have any bearing on your life. I share them because my experience challenged a lot of the things I was taught to believe about love, and I think my current beliefs are both truer and would benefit others seeing companionship.
We're taught in many modern societies from an absurdly young age that love is not something under our control, and that dating should be a process of trying to kindle love with different people until we meet "the one" with whom it takes off. In the slightly-less-fairytale corners of modern popular media, we might fund an admission that it's possible to influence love, feeding & tending the fire in better or worse ways. But it's still modeled as an uncontrollable force of nature, to be occasionally influenced but never tamed. I'll call this the "fire" model of love.
We're also taught (and non-boys are taught more stringently) a second contradictory model of love: that in a relationship, we need to both do things and be things in order to make our partner love us, and that if we don't, our partner's love for us will wither, and (especially if you're not a boy) it will be our fault. I'll call this the "appeal" model of love.
Now obviously both of these cannot be totally true at once, and plenty of popular media centers this contradiction, but there are really very few competing models on offer.
In my experience, however, it's possible to have "pre-meditated" love. In other words, to decide you want to love someone (or at least, try loving them), commit to that idea, and then actually wind up in love with them (and them with you, although obviously this second part is not directly under your control). I'll call this the "engineered" model of love.
Now, I don't think that the "fire" and "appeal" models of love are totally wrong, but I do feel their shortcomings often suggest poor & self-destructive relationship strategies. I do think the "fire" model is a decent model for *infatuation*, which is something a lot of popular media blur into love, and which drives many (but not all) of the feelings we normally associate with love (even as those feelings have other possible drivers too). I definitely experienced strong infatuation early on in my engineered relationship (ugh that sounds terrible but I'll stick with it; I promise no deception was involved). I continue to experience mild infatuation years later that waxes and wanes. It's not a stable foundation for a relationship but it can be a useful component of one (this at least popular media depicts often).
I'll continue these thoughts in a reply, by it might take a bit to get to it.
#relationships