Tootfinder

"While crop seed vaults are common around the world, nurseries for wild and native plants are rare, and many plant species quietly become extinct. This marks #Gurukula out as a Noah’s ark for endangered plant species."

Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions
Li Siyao, Yao Feng, Omid Tehari, Chen Change Loy, Michael J. Black
https://arxiv.org/abs/2507.23778 ht…

Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions
While current general-purpose 3D human models (e.g., SMPL-X) efficiently represent accurate human shape and pose, they lacks the ability to physically interact with the environment due to the kinematic nature. As a result, kinematic-based interaction models often suffer from issues such as interpenetration and unrealistic object dynamics. To address this limitation, we introduce a novel approach that embeds SMPL-X into a tangible entity capable of dynamic physical interactions with its surround…

While I'm copying yesterday's photos to my computer, I'll just share some more photos from my recent blog post.
I tried to put the bushes at the lake as framing elements into the #photos. I think it worked out quite okay. -- And while we were on this walk I imagined all the time where and how this could look at sunset or with fog.
Maybe I should go there a again a couple o…

Clarity Dawns: Human Beings, Nature, and Becoming
#becoming #BeBetter
https://muz4now.com/2019/clari…

Clarity Dawns: Human Beings, Nature, and Becoming
Stan Stewart - @muz4now

Driving factors of auditory category learning success
Nan Wang, Gangyi Feng
https://arxiv.org/abs/2506.01508 https://arxiv.org/pdf/25…

Driving factors of auditory category learning success
Our brain learns to update its mental model of the environment by abstracting sensory experiences for adaptation and survival. Learning to categorize sounds is one essential abstracting process for high-level human cognition, such as speech perception, but it is also challenging due to the variable nature of auditory signals and their dynamic contexts. To overcome these learning challenges and enhance learner performance, it is essential to identify the impact of learning-related factors in dev…

The Human Capital Ontology (Extended Abstract)
Shane Babcock, Maxwell Farrington, John Gugliotti
https://arxiv.org/abs/2507.21175 https://arxiv.org/pdf/250…

The Human Capital Ontology (Extended Abstract)
The Human Capital Ontology (HCO) is an ontology that represents data standards maintained and employed by the Office of Personnel Management (OPM) to represent Human Capital Operations and to classify job positions. The HCO is an extension of the Common Core Ontologies and the upper level Basic Formal Ontology (BFO). HCO provides representation of OPM Nature of Action (NOA) codes that are used to describe human resource personnel actions. HCO also represents Occupational Groups and Job Families…

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…

Human Mobility in Epidemic Modeling
Xin Lu, Jiawei Feng, Shengjie Lai, Petter Holme, Shuo Liu, Zhanwei Du, Xiaoqian Yuan, Siqing Wang, Yunxuan Li, Xiaoyu Zhang, Yuan Bai, Xiaojun Duan, Wenjun Mei, Hongjie Yu, Suoyi Tan, Fredrik Liljeros
https://arxiv.org/abs/2507.22799

Human Mobility in Epidemic Modeling
Human mobility forms the backbone of contact patterns through which infectious diseases propagate, fundamentally shaping the spatio-temporal dynamics of epidemics and pandemics. While traditional models are often based on the assumption that all individuals have the same probability of infecting every other individual in the population, a so-called random homogeneous mixing, they struggle to capture the complex and heterogeneous nature of real-world human interactions. Recent advancements in da…

Bayesian Inference for Spatially-Temporally Misaligned Data Using Predictive Stacking
Soumyakanti Pan, Sudipto Banerjee
https://arxiv.org/abs/2505.24397 ht…

Bayesian Inference for Spatially-Temporally Misaligned Data Using Predictive Stacking
Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is challenging due to the complex nature of exposure data. Recent technological advances have led to the collection of various indicators of air pollution at increasingly high spatial-temporal resolutions (e.g., daily averages of pollutant levels at spatial locations referenced by latitude-longitude). However, health outco…

A foundation model to predict and capture human cognition.
https://www.nature.com/articles/s41586-025-09215-4
And the reaction and criticism,

A foundation model to predict and capture human cognition - Nature
A computational model called Centaur, developed by fine-tuning a language model on a huge dataset called Psych-101, can predict and simulate human nature in experiments expressible in natural language, even in previously unseen situations.

"The most worrying possibility behind Earth’s [accelerating warming] is how the general nature of clouds may be changing in response to climbing temperatures. It’s a feedback loop that could potentially exacerbate warming and is one of the single biggest uncertainties in predicting future climate."

Global Warming Is Speeding Up and the World Is Feeling the Effects
Human-caused global warming has been increasing faster and faster since the 1970s.

Eine neue Studie zeigt die negativen Auswirkungen menschlicher Aktivitäten auf die biologische Vielfalt für alle Arten und Ökosysteme.
Menschliche Aktivitäten treiben den Verlust der biologischen Vielfalt sowohl direkt, als auch indirekt voran.
Via @…

The global human impact on biodiversity - Nature
Key measures of biodiversity were quantified and found to be affected by human pressures that shifted community composition and decreased local diversity across terrestrial, freshwater and marine ecosystems.

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen, Dongwon Jung, Hadi Askari, Wenxuan Zhou, Zhe Zhao, Muhao Chen
https://arxiv.org/abs/2507.22063

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software development and testing. However, recent studies have shown that these models are prone to generating vulnerable or even malicious code under adversarial settings. Existing red-teaming approaches rely on extensive human effort, limiting their scalability and practicality, and generally overlook the interactive nature of real-world AI-assisted programming, which of…

This https://arxiv.org/abs/2505.19301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control
Traditional Identity and Access Management (IAM) systems, primarily designed for human users or static machine identities via protocols such as OAuth, OpenID Connect (OIDC), and SAML, prove fundamentally inadequate for the dynamic, interdependent, and often ephemeral nature of AI agents operating at scale within Multi Agent Systems (MAS), a computational system composed of multiple interacting intelligent agents that work collectively. This paper posits the imperative for a novel Agentic AI I…

In Nature Human Behaviour, Peter Gleick calls on scientists who are able and willing to do so to speak out publicly against the Trump administration’s attack on science,
and argues that although dissent carries risks, it is riskier to stay silent.
http://go.nature.com/3FIV7cC

🇺🇦 #NowPlaying on KEXP's #JazzTheatre
Vijay Iyer:
🎵 Human Nature
#VijayIyer
https://vijayiyer.bandcamp.com/track/human-nature
https://open.spotify.com/track/6vT6GhO6th2JE3NBQRlhKL

Hear what the muse has to say: The muse is present. Stan Stewart is a pianist, composer, and songwriter. https://muz4now.com

Stan Stewart - aka @muz4now - the muse is present
Stan Stewart is a poet, musician, and human being who enjoys connecting with people and nature. Since his focus is on improvisational music, the inspiration he gets from these connections is often the source of his music.

(World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments
Abigail Greenbaum, Elizabeth Strickler, Victoria Patterson, Bolu Oluleye
https://arxiv.org/abs/2506.22988

(World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments
Emerging extended reality (XR) tools and platforms offer an exciting opportunity to align learning experiences in higher education with the futures in which students will pursue their goals. However, the dynamic nature of XR as subject matter challenges hierarchies and classroom practices typical of higher education. This instructional design practice paper reflects on how our team of faculty, learning experience designers, and user experience (UX) researchers implemented human-centered design …

This https://arxiv.org/abs/2505.11864 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Learning Pareto-Optimal Rewards from Noisy Preferences: A Framework for Multi-Objective Inverse Reinforcement Learning
As generative agents become increasingly capable, alignment of their behavior with complex human values remains a fundamental challenge. Existing approaches often simplify human intent through reduction to a scalar reward, overlooking the multi-faceted nature of human feedback. In this work, we introduce a theoretical framework for preference-based Multi-Objective Inverse Reinforcement Learning (MO-IRL), where human preferences are modeled as latent vector-valued reward functions. We formalize …

Remember how banning guns because of one mass shooting in 20 years didn't reduce violent crime? Well, I'm sure if they just keep banning everything that ever gets used in a violent crime, human nature will just magically change, right?
https://www.bbc.com/news/articles/clyvxxd4knjo

Australia fast-tracks first-ever machete ban after weekend attack
The ban follows a machete attack between gangs at a Melbourne shopping centre on Sunday afternoon

"Why Antidepressants Work Better for Some"
Key Facts:
Immune Pathways: Toll-like receptor and NF-κB pathways were consistently altered between responders and non-responders.
Neural Mechanisms: Signal transduction and GABAergic synapse pathways showed consistent changes with fluoxetine treatment.
Heterogeneity Noted: Patterns of gene expression varied across tissues, models, and individuals, emphasizing the need for larger, more targeted studies.
Paper: Sou…

Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses - Molecular Psychiatry
Genomic (and other ‘omic) data have provided valuable insights on the pharmacological signatures of antidepressant response, but results from individual studies are largely heterogeneous. In this work, we synthesized gene expression data for fluoxetine treatment in both human patients and rodent models, to better understand biological pathways affected by treatment, as well as those that may distinguish clinical or behavioral response. Following the PRISMA guidelines, we searched the Gene Exp…

To dig slightly deeper here, I think that there's a feedback loop between "fall in love/wait for your perfect match (and by the way girls the only career you should aspire to is the literally unattainable 'princess'" Disney stuff and this "my characters are complex I'm so sophisticated; they suffer but it's not intolerable and their lives are good enough despite the imperfections" crap that gets praised as so evocative of the human condition. In fact, I think it merely evokes the condition of its authors & fans who were poisoned by the Disney in their youth and who have remained bad as relationships ever since, though this is not exactly their fault. In any case, their white middle-aged wisdom-shaped-but-quite bitter and intricately-constructed-so-it's-hard-to-see-the-really-untrue-character-facets work ends up keeping their audience within the "romance is luck" cult by way of reassuring them that a middling romance with lots of doubt and complications is "just life" even though the author doesn't actually have any broader perspective on what life is than anyone else.
This has turned into a bit of a rant, but I think I'll just add that reading Mama by Nikkya Hargrove just before Dream State helped immensely to see how the distant & awkward parent-child relationships of the latter are not a product of human nature but instead of white western culture & capitalism.
(The defeatism about climate change is a whole nother dimension of wrong about Dream State, by that's a separate rant.)

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study
Karisa Parkington, Bazen G. Teferra, Marianne Rouleau-Tang, Argyrios Perivolaris, Alice Rueda, Adam Dubrowski, Bill Kapralos, Reza Samavi, Andrew Greenshaw, Yanbo Zhang, Bo Cao, Yuqi Wu, Sirisha Rambhatla, Sridhar Krishnan, Venkat Bhat
https:/…

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study
Thematic analysis provides valuable insights into participants' experiences through coding and theme development, but its resource-intensive nature limits its use in large healthcare studies. Large language models (LLMs) can analyze text at scale and identify key content automatically, potentially addressing these challenges. However, their application in mental health interviews needs comparison with traditional human analysis. This study evaluates out-of-the-box and knowledge-base LLM-based t…

Centuries-old mercury pollution hidden in the ocean threatens Arctic wildlife #Arctic

Centuries-old mercury pollution hidden in the ocean threatens Arctic wildlife
Despite global reductions in mercury emissions, mercury concentrations in Arctic wildlife continue to rise. A study published in Nature Communications by researchers from Aarhus University and the University of Copenhagen reveals that ocean currents may be transporting legacy mercury pollution to the Arctic—posing a long-term threat to ecosystems and human health.

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
Li Kang, Yuhan Zhao, Li Chen
https://arxiv.org/abs/2507.17290 https://arx…

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
Serendipity plays a pivotal role in enhancing user satisfaction within recommender systems, yet its evaluation poses significant challenges due to its inherently subjective nature and conceptual ambiguity. Current algorithmic approaches predominantly rely on proxy metrics for indirect assessment, often failing to align with real user perceptions, thus creating a gap. With large language models (LLMs) increasingly revolutionizing evaluation methodologies across various human annotation tasks, we…

🇺🇦 #NowPlaying on KEXP's #AfternoonShow
Madonna:
🎵 Human Nature
#Madonna
https://ellemaxwell.bandcamp.com/track/human-nature
https://open.spotify.com/track/4Cna7QxOOTNnylVHLtShCi

For more than a century, putrid fumes emanated from
the “sewer of the Ruhr”,
creating a pungent whiff that assaulted towns throughout Germany’s industrial heartland.
But today, the Emscher bears little resemblance to Europe’s dirtiest river.
Water that used to be fouled by factory waste and human excrement have been free from effluent since 2021.
The river system, the main part of which was once considered biologically dead, is witnessing the return of an abun…

Direct observation of the crossed interhemispheric transfer of the left-right mirror-images in human vision
Albert Le Floch, Guy Ropars
https://arxiv.org/abs/2507.08703

Direct observation of the crossed interhemispheric transfer of the left-right mirror-images in human vision
Symmetry breaking is common in animal and human brains where the lack of asymmetry often perturbs behavioral and cognitive functions. In particular, the ubiquity of mirror-image confusion in young children, which often persists in dyslexia, is established. However, the very existence of these symmetric mirror-images and their perceptual or memory nature remain controversial. Here, using the noise-activated afterimage method, we demonstrate that a dyslexic with mirror-images is an ideal candidat…

Bilateral Collaboration with Large Vision-Language Models for Open Vocabulary Human-Object Interaction Detection
Yupeng Hu, Changxing Ding, Chang Sun, Shaoli Huang, Xiangmin Xu
https://arxiv.org/abs/2507.06510

Bilateral Collaboration with Large Vision-Language Models for Open Vocabulary Human-Object Interaction Detection
Open vocabulary Human-Object Interaction (HOI) detection is a challenging task that detects all triplets of interest in an image, even those that are not pre-defined in the training set. Existing approaches typically rely on output features generated by large Vision-Language Models (VLMs) to enhance the generalization ability of interaction representations. However, the visual features produced by VLMs are holistic and coarse-grained, which contradicts the nature of detect…

Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoning
Dongyang Guo, Yasmeen Abdrabou, Enkeleda Thaqi, Enkelejda Kasneci
https://arxiv.org/abs/2507.18252

Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoning
Eye-tracking data reveals valuable insights into users' cognitive states but is difficult to analyze due to its structured, non-linguistic nature. While large language models (LLMs) excel at reasoning over text, they struggle with temporal and numerical data. This paper presents a multimodal human-AI collaborative framework designed to enhance cognitive pattern extraction from eye-tracking signals. The framework includes: (1) a multi-stage pipeline using horizontal and vertical segmentation alo…

Weird Greco 🇬🇷
怪异希腊 🇬🇷
📷 Nikon FE
🎞️FOMAPAN Action 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Rethinking Ecological Measures Of Functional Diversity
Ines Meraoumia, Adji Bousso Dieng
https://arxiv.org/abs/2506.17839 https://arx…

Rethinking Ecological Measures Of Functional Diversity
Understanding functional diversity, the range and variability of species' roles and actions within their communities, is key to predicting and preserving the functions that sustain both nature and human well-being. In this paper, we provide a comprehensive review of the literature on functional diversity measurement. We begin by consolidating essential criteria that effective measures of functional diversity should meet. We then evaluate fifteen widely used functional diversity metrics against …

Coming tomorrow: a new song (preview from my upcoming folksong album) and song video
#MusicVideo
Watch for it on https://muz4now.com/?utm_source=dl…

Stan Stewart - aka @muz4now - the muse is present
Stan Stewart is a poet, musician, and human being who enjoys connecting with people and nature. Since his focus is on improvisational music, the inspiration he gets from these connections is often the source of his music.

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
Chenhui Deng, Yun-Da Tsai, Guan-Ting Liu, Zhongzhi Yu, Haoxing Ren
https://arxiv.org/abs/2506.05566

ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
Recent advances in large language models (LLMs) have enabled near-human performance on software coding benchmarks, but their effectiveness in RTL code generation remains limited due to the scarcity of high-quality training data. While prior efforts have fine-tuned LLMs for RTL tasks, they do not fundamentally overcome the data bottleneck and lack support for test-time scaling due to their non-reasoning nature. In this work, we introduce ScaleRTL, the first reasoning LLM for RTL coding that scal…

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
Jiarui Li, Zixiang Yin, Haley Smith, Zhengming Ding, Samuel J. Landry, Ramgopal R. Mettu
https://arxiv.org/abs/2507.03197

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
CD8+ "killer" T cells and CD4+ "helper" T cells play a central role in the adaptive immune system by recognizing antigens presented by Major Histocompatibility Complex (pMHC) molecules via T Cell Receptors (TCRs). Modeling binding between T cells and the pMHC complex is fundamental to understanding basic mechanisms of human immune response as well as in developing therapies. While transformer-based models such as TULIP have achieved impressive performance in this domain, their black-box nature …

Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
Chengyuan Zhang, Cathy Wu, Lijun Sun
https://arxiv.org/abs/2506.14762

Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
Accurate and interpretable car-following models are essential for traffic simulation and autonomous vehicle development. However, classical models like the Intelligent Driver Model (IDM) are fundamentally limited by their parsimonious and single-regime structure. They fail to capture the multi-modal nature of human driving, where a single driving state (e.g., speed, relative speed, and gap) can elicit many different driver actions. This forces the model to average across distinct behaviors, red…

Neutral theory of cooperators
Jordi Pi\~nero, Artemy Kolchinsky, Sidney Redner, Ricard Sol\'e
https://arxiv.org/abs/2506.09737 https://

Neutral theory of cooperators
Mutualistic interactions are widespread in nature, from plant communities and microbiomes to human organizations. Along with competition for resources, cooperative interactions shape biodiversity and contribute to the robustness of complex ecosystems. We present a stochastic neutral theory of cooperator species. Our model shares with the classic neutral theory of biodiversity the assumption that all species are equivalent, but crucially differs in requiring cooperation between species for repli…