Tootfinder

🦠 Microbiologists discover new species of methane-producing archaea in the human gut
https://phys.org/news/2025-04-microbiologists-species-methane-archaea-human.html

Microbiologists discover new species of methane-producing archaea in the human gut
An international team of microbiologists from the Medical University of Graz, the DSMZ—German Collection of Microorganisms and Cell Cultures (Braunschweig, Germany)—and the University of Illinois (U.S.) has identified and described a previously unknown species of methane-producing archaea in the human gut: Methanobrevibacter intestini sp. nov. (strain WWM1085).

So Builder . ai Mechanical Turked things and Microsoft (and others) were none the wiser.
Due diligence: boring stuff that when you skip it with catch up with you fast.
“Builder . ai’s platform relied on around 700 engineers based in India who manually wrote code based on customer requests. Despite the company marketing it as AI-generated, most of the work was done by humans behind the scenes.”

London AI startup Builder.ai collapses after 'human-powered' tech revelation
London AI startup Builder.ai collapses after 'human-powered' tech revelation

Can LLMs and humans be friends? Uncovering factors affecting human-AI intimacy formation
Yeseon Hong, Junhyuk Choi, Minju Kim, Bugeun Kim
https://arxiv.org/abs/2505.24658

Can LLMs and humans be friends? Uncovering factors affecting human-AI intimacy formation
Large language models (LLMs) are increasingly being used in conversational roles, yet little is known about how intimacy emerges in human-LLM interactions. Although previous work emphasized the importance of self-disclosure in human-chatbot interaction, it is questionable whether gradual and reciprocal self-disclosure is also helpful in human-LLM interaction. Thus, this study examined three possible aspects contributing to intimacy formation: gradual self-disclosure, reciprocity, and naturalnes…

I consider these kinds of events to be nearly useless symbolism, preaching to the choir.
I do accept that these events are useful as means to meet others, but one should not expect these events to have even the slightest impact on the maga/white-nationalist/musk-ites... Nor do I think they have much impact on those who are in "the middle" and do not particularly engage in politics.
"Nearly 1,000 gather at Main Beach to create ‘Resist!’ human banner protesting Trum…

Nearly 1,000 gather at Main Beach to create ‘Resist!’ human banner protesting Trump administration
Around 1,000 people gathered Saturday morning at Santa Cruz Main Beach to spell out the word “Resist!” The event, organized by Indivisible Santa Cruz County, aimed to protest the Trump administration and celebrate Santa Cruz Pride’s 50th anniversary.

So, I climbed to the top of the pyramid of pain -- now what?
Vasilis Katos, Emily Rosenorn-Lanng, Jane Henriksen-Bulmer, Ala Yankouskaya
https://arxiv.org/abs/2505.24685

So, I climbed to the top of the pyramid of pain -- now what?
This paper explores the evolving dynamics of cybersecurity in the age of advanced AI, from the perspective of the introduced Human Layer Kill Chain framework. As traditional attack models like Lockheed Martin's Cyber Kill Chain become inadequate in addressing human vulnerabilities exploited by modern adversaries, the Humal Layer Kill Chain offers a nuanced approach that integrates human psychology and behaviour into the analysis of cyber threats. We detail the eight stages of the Human Layer Ki…

Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs
Chenjun Xu, Bingbing Wen, Bin Han, Robert Wolfe, Lucy Lu Wang, Bill Howe
https://arxiv.org/abs/2506.00582

Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs
Psychology research has shown that humans are poor at estimating their performance on tasks, tending towards underconfidence on easy tasks and overconfidence on difficult tasks. We examine three LLMs, Llama-3-70B-instruct, Claude-3-Sonnet, and GPT-4o, on a range of QA tasks of varying difficulty, and show that models exhibit subtle differences from human patterns of overconfidence: less sensitive to task difficulty, and when prompted to answer based on different personas -- e.g., expert vs laym…

Vivodyne, which uses AI and robots to grow human tissues in the lab for drug discovery and development, raised a $40M Series A, taking its total funding to $78M (Katherine Davis/Axios)
https://www.axios.com/pro/biotech-deals/2025/05…

Vivodyne raises $40M for human tissue drug testing
It's seeing heightened demand following the FDA's plans to phase out animal testing requirements.

Weak but influential: Nonlinear contributions of structural connectivity to human cognitive abilities and brain functions
Rong Wang, Zhao Chang, Xuechun Liu, Daniel Kristanto, \'Etienne G\'erard Guy Gartner, Xinyang Liu, Mianxin Liu, Ying Wu, Ming Lui, Changsong Zhou
https://arxiv.org/abs/2505.24125

Weak but influential: Nonlinear contributions of structural connectivity to human cognitive abilities and brain functions
Diverse human cognitive abilities are rooted in brain structural connectivity which has weights spanning several orders of magnitude. However, due to false-positive challenges in tractography, weak connectivity has been often treated as noise and ignored - despite its prevalence across mammalian brains. Here we show that weak connectivity significantly predicts human cognitive abilities and supports brain functions through amplification of its small weight in a nonlinear manner. Using the Human…

FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
Longyan Wu, Checheng Yu, Jieji Ren, Li Chen, Ran Huang, Guoying Gu, Hongyang Li
https://arxiv.org/abs/2506.01941

FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation
Enabling robots with contact-rich manipulation remains a pivotal challenge in robot learning, which is substantially hindered by the data collection gap, including its inefficiency and limited sensor setup. While prior work has explored handheld paradigms, their rod-based mechanical structures remain rigid and unintuitive, providing limited tactile feedback and posing challenges for human operators. Motivated by the dexterity and force feedback of human motion, we propose FreeTacMan, a human-ce…

I just ran across this on LinkedIn: yet another study showing that LLMs embed and amplify human biases in the training data—this time in resume screening.
Yet this is the technology Trump, Musk, and DOGE want to use to rewrite things like HUD regulations and to replace human support agents.

Gender, race, and intersectional bias in AI resume screening via language model retrieval
Kyra Wilson and Aylin Caliskan examine gender, race, and intersectional bias in AI resume screening and suggest protective policies.

reality_mining: Reality mining proximity network (2004)
A network of human proximities among students at Massachusetts Institute of Technology (MIT), as measured by personal mobile phones. Nodes represent people (students from the Media Lab and the Sloan Business School) and an edge connects a pair if the two devices made a Bluetooth handshake at the time. Edges are timestamped.
This network has 96 nodes and 1086404 edges.
Tags: Social, Offline, Unweighted, Timestamps

Towards a unified user modeling language for engineering human centered AI systems
Aaron Conrardy, Alfredo Capozucca, Jordi Cabot
https://arxiv.org/abs/2505.24697

Towards a unified user modeling language for engineering human centered AI systems
In today's digital society, personalization has become a crucial aspect of software applications, significantly impacting user experience and engagement. A new wave of intelligent user interfaces, such as AI-based conversational agents, has the potential to enable such personalization beyond what other types of interfaces could offer in the past. Personalization requires the ability to specify a complete user profile, covering as many dimensions as possible, such as potential accessibility cons…

🇺🇦 #NowPlaying on KEXP's #90TEEN
Tokyo Tea Room:
🎵 I’m Just Human
#TokyoTeaRoom
https://niceguysweare.bandcamp.com/track/im-just-human
https://open.spotify.com/track/4E3kfvhz0xpaCy2wLuMjFq

Love this, by D.J. Grothe
We are truly only just getting started. All we have to do is to fail to kill everyone, and things will get better.
"Human civilization has existed for only 3% of the time that anatomically modern humans have existed. And modern industrial civilization has existed for just 2% of that 3% — just 0.06% of the time that anatomically modern humans have existed. Maybe we’re just getting started!"

heise | heise Update vom 30. Mai 2025: Lesetipps fürs Wochenende
Der wöchentliche Newsletter von heise mit Schutz vor "Human Risk", Steuer-Apps, Deutschland-Stack, Synology-RAID nachbilden, Gefahr von Online-Glücksspiel

Webinars this Wed and Thu tackle AI's impact on archives—Sara and Ben Brumfield of FromThePage on combining AI and human crowdsourcing, and yours truly on the long-term threat to cultural heritage of irresponsible AI use. More at https://blog.still-water.net/should-yo

(1/3) Please join me today on Zoom at 12pm ET / 11am CT / 10am MT / 9am PT for "Beyond the Algorithmic Feed," a free MediaEd Club webinar for the Media Education Lab:
https://mediaeducationlab.com/index.php/events/beyond-algorithmic-feed
While som…

I understood this in principle but for some reason this graph really drove home the shape of the problem. https://vis.social/@infobeautiful/114614345328627391

Information Is Beautiful (@infobeautiful@vis.social)
Attached: 1 image If you're aged 30 or more, then 50% of all human fossil fuel emissions happened during your lifetime

⏰ SemDH Workshop is about to take place at ESWC25 in the beautiful city of Portoroz, Slovenia on Monday, June 2nd, 2025!
Check out the full, detailed program at https://semdh.github.io/program.html
The keynote will be held by Laura Hollink, Human-Centered Data Analytics group leade…

From KPIs to trends, make your MySQL data shine! Syed Usman Ahmad shows how to use Grafana dashboards for powerful, human-readable visualizations at #SCaLE 22x. https://phpa.me/22xreg

Comparative analysis of computational approaches for predicting Transthyretin transcription activators and human dopamine D1 receptor antagonists
Mariya L. Ivanova, Nicola Russo, Konstantin Nikolic
https://arxiv.org/abs/2506.01137

Comparative analysis of computational approaches for predicting Transthyretin transcription activators and human dopamine D1 receptor antagonists
The study expands the application of scikit-learn-based machine learning (ML) to the prediction of small biomolecule functionalities based on Carbon 13 isotope (13C) NMR spectroscopy data derived from Simplified Molecular Input Line Entry System (SMILES) notations. The methodology previously demonstrated by predicting dopamine D1 receptor antagonists was upgraded with addition of new molecular features derived from the PubChem database. The enhanced ML model obtained 75.8% Accuracy, 84.2% Preci…

From Bill McKibben
"Let me state it plainly: we are rushing into the most dangerous period in human history, and the Trump administration seems determined that we do it blindly. It’s inconceivably stupid, and it’s entirely real. And the planet doesn’t care: physics will not cut us any slack because we elected a moron."

Meanwhile, back in the real world
There's too much carbon in the atmosphere, so it's hot

AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents
Hanjun Luo, Shenyu Dai, Chiming Ni, Xinfeng Li, Guibin Zhang, Kun Wang, Tongliang Liu, Hanan Salam
https://arxiv.org/abs/2506.00641

AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents
Despite the rapid advancement of LLM-based agents, the reliable evaluation of their safety and security remains a significant challenge. Existing rule-based or LLM-based evaluators often miss dangers in agents' step-by-step actions, overlook subtle meanings, fail to see how small issues compound, and get confused by unclear safety or security rules. To overcome this evaluation crisis, we introduce \sys, a universal, training-free, memory-augmented reasoning framework that empowers LLM evaluator…

#Ambisonics algorithm: Can it beat human hearing? https://www.theneurotimes.com/ambisonics-algorithm-human-hearing/ "Can the ambisonics algorithm in AudioDome re…

Ambisonics Algorithm: Can It Beat Human Hearing? - The Neuro Times
Can the ambisonics algorithm in AudioDome recreate 3D sound more precisely than human perception? Explore the science behind this immersive tech.

AI isn’t an existential threat to humanity, capitalism and corporations are.
You see, we created capitalism, a religion modeled on cancer, and the corporation, a new, artificial species; a parasite that co-opts human beings to do its bidding; an organism that’s psychopathic by design and grows by extracting from and exploiting us and our habitat.
And we now find ourselves ruled by this religion and driven to ruin by these parasites as they drain our humanity, destroy our habitat,…

Neuralink raised a $650M Series E from ARK Invest, Founders Fund, G42, Human Capital, Sequoia, Thrive, and others; it was reportedly valued at ~$9B pre-money (Maxwell Zeff/TechCrunch)
https://techcrunch.com/2025/06/02/elon-musks-neuralink-closes-a-65…

Elon Musk's Neuralink closes a $650M Series E | TechCrunch
Elon Musk's brain chip implant startup Neuralink raised a $650 million Series E funding round, the company announced.

Someone in my LinkedIn network posted this, and I have no inkling if it is genuine or sarcasm (see: Poe's Law).
Full text of the post in the image Alt Text.
NOTE: Please do not dogpile this person due to my toot.
#LLMs #WorkerReplacement

I just ran across this on LinkedIn: yet another study showing that LLMs embed and amplify human biases in the training data—this time in resume screening.
Yet this is the technology Trump, Musk, and DOGE want to use to rewrite things like HUD regulations and to replace human support agents.

Gender, race, and intersectional bias in AI resume screening via language model retrieval
Kyra Wilson and Aylin Caliskan examine gender, race, and intersectional bias in AI resume screening and suggest protective policies.

Back stretching safety officer, on duty! :ablobcatlurk:

Hierarchical Intention-Aware Expressive Motion Generation for Humanoid Robots
Lingfan Bao, Yan Pan, Tianhu Peng, Chengxu Zhou
https://arxiv.org/abs/2506.01563

Hierarchical Intention-Aware Expressive Motion Generation for Humanoid Robots
Effective human-robot interaction requires robots to identify human intentions and generate expressive, socially appropriate motions in real-time. Existing approaches often rely on fixed motion libraries or computationally expensive generative models. We propose a hierarchical framework that combines intention-aware reasoning via in-context learning (ICL) with real-time motion generation using diffusion models. Our system introduces structured prompting with confidence scoring, fallback behavio…

"Alvin, the world’s longest-operating and most productive human-occupied deep-sea submersible, with more than 5,000 dives completed over 60 years of operation ... recently underwent a significant upgrade, allowing it to reach depths of up to 6,500 meters—surpassing its previous limit of 4,500 meters." - Eos #geology

An Upgraded Alvin Puts New Ocean Depths Within Reach
The newly retooled submersible, which has already returned fascinating new findings from Earth’s watery depths, is opening more of the deep ocean to direct human exploration.

This https://arxiv.org/abs/2505.18422 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A Task-Driven Human-AI Collaboration: When to Automate, When to Collaborate, When to Challenge
According to several empirical investigations, despite en-hancing human capabilities, human-AI cooperation fre-quently falls short of expectations and fails to reach true synergy. We propose a task-driven framework that reverses prevalent approaches by assigning AI roles according to how the task's requirements align with the capabilities of AI technology. Three major AI roles are identified through task analysis across risk and complexity dimensions: au-tonomous, assistive/collaborative, and a…

This https://arxiv.org/abs/2412.18407 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

A Statistical Framework for Ranking LLM-Based Chatbots
Large language models (LLMs) have transformed natural language processing, with frameworks like Chatbot Arena providing pioneering platforms for evaluating these models. By facilitating millions of pairwise comparisons based on human judgments, Chatbot Arena has become a cornerstone in LLM evaluation, offering rich datasets for ranking models in open-ended conversational tasks. Building upon this foundation, we propose a statistical framework that incorporates key advancements to address specif…

Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction
Anam Hashmi, Julia Dietlmeier, Kathleen M. Curran, Noel E. O'Connor
https://arxiv.org/abs/2505.23872

Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction
Attention is a fundamental component of the human visual recognition system. The inclusion of attention in a convolutional neural network amplifies relevant visual features and suppresses the less important ones. Integrating attention mechanisms into convolutional neural networks enhances model performance and interpretability. Spatial and channel attention mechanisms have shown significant advantages across many downstream tasks in medical imaging. While existing attention modules have proven …

Self-Supervised Speech Quality Assessment (S3QA): Leveraging Speech Foundation Models for a Scalable Speech Quality Metric
Mattson Ogg, Caitlyn Bishop, Han Yi, Sarah Robinson
https://arxiv.org/abs/2506.01655

Self-Supervised Speech Quality Assessment (S3QA): Leveraging Speech Foundation Models for a Scalable Speech Quality Metric
Methods for automatically assessing speech quality are critical for many human language technologies. Behavioral ratings provided by human raters (e.g., mean opinion scores; MOS) are considered the gold standard, but they are susceptible to variability between individual raters, cannot easily be generalized across corpora, and are labor-intensive to collect, thus limiting the acoustic challenges they can quantify. Here, we present a new, scalable method for automatically assessing speech qualit…

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Rolf Drechsler
https://arxiv.org/abs/2505.23311 https://

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Verification is one of the central tasks in circuit and system design. While simulation and emulation are widely used, complete correctness can only be ensured based on formal proof techniques. But these approaches often have very high run time and memory requirements. Recently, Polynomial Formal Verification (PFV) has been introduced showing that for many instances of practical relevance upper bounds on needed resources can be given. But proofs have to be provided that are human-readable. He…

Dang it…is there a human-readable data format that is basically YAML syntax but the simple featureset of JSON (plus comments)?
I want something concise and Markdown-ish, made for human editing, like YAML, but without all of YAML’s…er, specialness.
EDIT: To be clear, this is for •primary content•, not configuration. It should •feel• like working with Markdown; it’s just that the output needs to be array-and-dict-shaped instead of HTML-shaped. (Lots of good suggestions in the replies already! TOML and KDL and are clear crowd favorites.)

The updated budget reiterated Trump’s pursuit of deep reductions for nearly every major federal agency,
reserving its steepest cuts for foreign aid,
medical research,
tax enforcement
and a slew of anti-poverty programs, including rental assistance.
The White House restated its plan to seek a $33 billion cut at the Department of Housing and Urban Development, for example,
and another $33 billion reduction at the Department of Health and Human Services.

Trump Officials Unveil Budget Cuts to Aid for Health, Housing and Research
The new blueprint shows that a vast array of education, health, housing and labor programs would be hit, including aid for college and cancer research.

Health and Human Services head RFK Jr threatens that publicly funded scientists may be stopped from publishing in leading medical journals.
https://www.theguardian.com/us-news/2025/may/28/rfk-jr-medical-journals

Quanta Magazine Staff Writer Yasemin Saplakoglu describes the various ongoing inter-disciplinary efforts to advance our scientific understanding of the Human brain. Computer scientists and computational neuroscientists collaborate as the latter borrow mathematical models from the former, and studies ways to incorporate new biological data to enhance, or supplant existing computational models.
"AI Is Nothing Like a Brain, and That's OK."

AI Is Nothing Like a Brain, and That’s OK | Quanta Magazine
The brain’s astounding cellular diversity and networked complexity could show how to make AI better.

This https://arxiv.org/abs/2503.14328 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Risk-Sensitive Model Predictive Control for Interaction-Aware Planning -- A Sequential Convexification Algorithm
This paper considers risk-sensitive model predictive control for stochastic systems with a decision-dependent distribution. This class of systems is commonly found in human-robot interaction scenarios. We derive computationally tractable convex upper bounds to both the objective function, and to frequently used penalty terms for collision avoidance, allowing us to efficiently solve the generally nonconvex optimal control problem as a sequence of convex problems. Simulations of a robot navigatin…

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa RYu
https://arxiv.org/abs/2506.00056

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Artificial intelligence (AI) is reshaping inverse design across manufacturing domain, enabling high-performance discovery in materials, products, and processes. However, purely data-driven approaches often struggle in realistic settings characterized by sparse data, high-dimensional design spaces, and nontrivial physical constraints. This perspective argues for a new generation of design systems that transcend black-box modeling by integrating domain knowledge, physics-informed learning, and in…

This https://arxiv.org/abs/2406.15119 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation
Speech emotion recognition (SER) plays a crucial role in human-computer interaction. The emergence of edge devices in the Internet of Things (IoT) presents challenges in constructing intricate deep learning models due to constraints in memory and computational resources. Moreover, emotional speech data often contains private information, raising concerns about privacy leakage during the deployment of SER models. To address these challenges, we propose a data distillation framework to facilitate…

Energy-Oriented Computing Architecture Simulator for SNN Training
Yunhao Ma (Pengcheng Laboratory, Southern University of Science and Technology), Wanyi Jia (Pengcheng Laboratory, Southern University of Science and Technology), Yanyu Lin (Pengcheng Laboratory), Wenjie Lin (Pengcheng Laboratory), Xueke Zhu (Pengcheng Laboratory), Huihui Zhou (Pengcheng Laboratory), Fengwei An (Southern University of Science and Technology)

Energy-Oriented Computing Architecture Simulator for SNN Training
With the growing demand for intelligent computing, neuromorphic computing, a paradigm that mimics the structure and functionality of the human brain, offers a promising approach to developing new high-efficiency intelligent computing systems. Spiking Neural Networks (SNNs), the foundation of neuromorphic computing, have garnered significant attention due to their unique potential in energy efficiency and biomimetic neural processing. However, current hardware development for efficient SNN train…

[former top exec at well-known human-rights org] noted the frustration inherent in trying to draw evenhanded distinctions that were once elementary in the human-rights world. “Hamas has an obligation under international law not to use human shields and to distinguish between military and civilian targets,” this person, who asked not to be identified to avoid further alienating former colleagues, said. “But if you bring this up internally, it’s framed as a distraction, an Israeli talking poin…

Joint space-time modelling for upper daily maximum and minimum temperature record-breaking
Jorge Castillo-Mateo (University of Zaragoza), Zeus Gracia-Tabuenca (University of Zaragoza), Jes\'us As\'in (University of Zaragoza), Ana C. Cebri\'an (University of Zaragoza), Alan E. Gelfand (Duke University)
https://arxiv.o…

Joint space-time modelling for upper daily maximum and minimum temperature record-breaking
Record-breaking temperature events are now frequently in the news, proffered as evidence of climate change, and often bring significant economic and human impacts. Our previous work undertook the first substantial spatial modelling investigation of temperature record-breaking across years for any given day within the year, employing a dataset consisting of over sixty years of daily maximum temperatures across peninsular Spain. That dataset also supplies daily minimum temperatures (which, in fac…

When I finally reach someone in the bureaucracy that treats me like a human, I gush with gratitude.
This is to say: I am probably very easy to manipulate by corporations.

Can AI erase the tedium of managing digital collections without also erasing what makes them distinctive? Find out in this recording of last month's webinar with Sara and Ben Brumfield of FromThePage, who explore the good, bad, and ugly of AI in archives.
https://digitalc…

This https://arxiv.org/abs/2409.18745 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A study on the effects of mixed explicit and implicit communications in human-virtual-agent interactions
Communication between humans and robots (or virtual agents) is essential for interaction and often inspired by human communication, which uses gestures, facial expressions, gaze direction, and other explicit and implicit means. This work presents an interaction experiment where humans and virtual agents interact through explicit (gestures, manual entries using mouse and keyboard, voice, sound, and information on screen) and implicit (gaze direction, location, facial expressions, and raise of ey…

This https://arxiv.org/abs/2505.23018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMM_…

EmotionTalk: An Interactive Chinese Multimodal Emotion Dataset With Rich Annotations
In recent years, emotion recognition plays a critical role in applications such as human-computer interaction, mental health monitoring, and sentiment analysis. While datasets for emotion analysis in languages such as English have proliferated, there remains a pressing need for high-quality, comprehensive datasets tailored to the unique linguistic, cultural, and multimodal characteristics of Chinese. In this work, we propose \textbf{EmotionTalk}, an interactive Chinese multimodal emotion datase…

this!! make something mediocre and imperfect and human, because you care. https://dansinker.com/posts/2025-05-23-who-cares/
(found this via @…’s …

A mean field game model with non-local spatial interactions and resources accumulation
Daria Ghilli, Fausto Gozzi, Cristiano Ricci, Giovanni Zanco
https://arxiv.org/abs/2506.01200

A mean field game model with non-local spatial interactions and resources accumulation
We study a family of Mean Field Games arising in modeling the behavior of strategic economic agents which move across space maximizing their utility from consumption and have the possibility to accumulate resources for production (such as human capital). The resulting mean field game PDE system is not covered in the actual literature on the topic as it displays weaker assumptions on the regularity of the data (in particular Lipschitz continuity and boundedness of the objective are lost), state …

#Blakes7 Series C, Episode 09 - Sarcophagus
ALIEN: [Her robes start blowing as if a breeze had sprung up] I thought you were the clever one. You're a fool, like Tarrant. The pain Tarrant is experiencing ... visualize that pain and much more. [Shot of Cally tossing her head back and forth.] You're as close to death as you have ever been. Think about human death, Avon. Irrevocable…

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

This https://arxiv.org/abs/2504.11918 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Deep learning to improve the discovery of near-Earth asteroids in the Zwicky Transient Facility
We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. Our work aims to minimize the dependency on human intervention of the current approach adopted by the Zwicky Transient Facility (ZTF). The target NEAs have a high proper motion of up to tens of degrees per day and thus appear as streaks of light in the images. We trained our CNNs to detect these streaks using three dat…

Google has been downgrading the search results of smaller web sites offering human-written quality information, claims Nate Hake of Travel Lemming in a long explanation, citing many sources and developments.
Many of these changes appear to happen when #Google embraced #AI and removed the "hum…

This https://arxiv.org/abs/2505.12018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Human Study of Cognitive Biases in CTF Challenges
Cybersecurity training has become a crucial part of computer science education and industrial onboarding. Capture the Flag (CTF) competitions have emerged as a valuable, gamified approach for developing and refining the skills of cybersecurity and software engineering professionals. However, while CTFs provide a controlled environment for tackling real world challenges, the participants' decision making and problem solving processes remain under explored. Recognizing that psychology may play a …

Predicting Empirical AI Research Outcomes with Language Models
Jiaxin Wen, Chenglei Si, Yueh-han Chen, He He, Shi Feng
https://arxiv.org/abs/2506.00794 htt…

Predicting Empirical AI Research Outcomes with Language Models
Many promising-looking ideas in AI research fail to deliver, but their validation takes substantial human labor and compute. Predicting an idea's chance of success is thus crucial for accelerating empirical AI research, a skill that even expert researchers can only acquire through substantial experience. We build the first benchmark for this task and compare LMs with human experts. Concretely, given two research ideas (e.g., two jailbreaking methods), we aim to predict which will perform better…

I read Human by Brett Hodentt (@…) and enjoyed it. A fun read which also raised interesting issues. Here is my #review

What factors are increasing zoonosis emergence? (Diseases transmitted from animals to human)
#environment #forest #deforestation

Quality assessment of 3D human animation: Subjective and objective evaluation
Rim Rekik, Stefanie Wuhrer, Ludovic Hoyet, Katja Zibrek, Anne-H\'el\`ene Olivier
https://arxiv.org/abs/2505.23301

Quality assessment of 3D human animation: Subjective and objective evaluation
Virtual human animations have a wide range of applications in virtual and augmented reality. While automatic generation methods of animated virtual humans have been developed, assessing their quality remains challenging. Recently, approaches introducing task-oriented evaluation metrics have been proposed, leveraging neural network training. However, quality assessment measures for animated virtual humans that are not generated with parametric body models have yet to be developed. In this contex…

PB&J: Peanut Butter and Joints for Damped Articulation
Avery S. Williamson, Michael J. Bennington, Ravesh Sukhnandan, Mrinali Nakhre, Yuemin Mao, Victoria A. Webster-Wood
https://arxiv.org/abs/2505.24860

PB&J: Peanut Butter and Joints for Damped Articulation
Many bioinspired robots mimic the rigid articulated joint structure of the human hand for grasping tasks, but experience high-frequency mechanical perturbations that can destabilize the system and negatively affect precision without a high-frequency controller. Despite having bandwidth-limited controllers that experience time delays between sensing and actuation, biological systems can respond successfully to and mitigate these high-frequency perturbations. Human joints include damping and stif…

I made another foray into the ethics of AI, this time with my colleagues Jan-Willem van der Rijt and Bram Vaassen.
https://arxiv.org/abs/2503.05723
We argue that some interactions with chatbots involve a kind of offense to users' dignity. When we treat chatbots as if they were fello…

This https://arxiv.org/abs/2505.22767 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

In Dialogue with Intelligence: Rethinking Large Language Models as Collective Knowledge
Large Language Models (LLMs) are typically analysed through architectural, behavioural, or training-data lenses. This article offers a theoretical and experiential re-framing: LLMs as dynamic instantiations of Collective human Knowledge (CK), where intelligence is evoked through dialogue rather than stored statically. Drawing on concepts from neuroscience and AI, and grounded in sustained interaction with ChatGPT-4, I examine emergent dialogue patterns, the implications of fine-tuning, and the …

AI doesn’t learn like we do. GoPro'd toddlers see mostly knees—but they can ID a dog after a few glimpses, while LLMs need billions of examples. Neuroscience suggests AI intelligence is gathered very differently than ours https://www.linkedin.com/p…

An AI machine has no idea what it means to be human.
Instruct it not to address you by name. Ask it to call itself AI, to speak in the third person, and to avoid emotional or cognitive terms.
https://theconversation.com/we-need-to

«AI systems are an attack on workers, climate goals, our information environment, and civil liberties. Rather than enhancing our human qualities, these systems degrade our social relations, and undermine our capacity for empathy and care.»
Nice writing by @…!
https://thedabbler.patatas.ca/pages/ai-is-dehumanization-technology.html

This https://arxiv.org/abs/2505.18893 has been replaced.
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Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects
Conventional AI evaluation approaches concentrated within the AI stack exhibit systemic limitations for exploring, navigating and resolving the human and societal factors that play out in real world deployment such as in education, finance, healthcare, and employment sectors. AI capability evaluations can capture detail about first-order effects, such as whether immediate system outputs are accurate, or contain toxic, biased or stereotypical content, but AI's second-order effects, i.e. any long…

This https://arxiv.org/abs/2502.05368 has been replaced.
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Otter: Generating Tests from Issues to Validate SWE Patches
While there has been plenty of work on generating tests from existing code, there has been limited work on generating tests from issues. A correct test must validate the code patch that resolves the issue. This paper focuses on the scenario where that code patch does not yet exist. Doing so supports two major use-cases. First, it supports TDD (test-driven development), the discipline of "test first, write code later" that has well-documented benefits for human software engineers. Second, it als…

Adult human being with a Winnie the Pooh T-shirt. We are not the same species.

Dang it…is there a human-readable data format that is basically YAML syntax but the simple featureset of JSON (plus comments)?
I want something concise and Markdown-ish, made for human editing, like YAML, but without all of YAML’s…er, specialness.
EDIT: To be clear, this is for •primary content•, not configuration. It should •feel• like working with Markdown; it’s just that the output needs to be array-and-dict-shaped instead of HTML-shaped. (Lots of good suggestions in the replies already! TOML and KDL and are clear crowd favorites.)

New paper alert:
Finkel & Lamm, Cultural evolution beyond the individual: what human collective knowledge adds to high fidelity copying.
This is the third in the Distributed Adaptation series.
Many thanks to the diligent reviewers! #philbio #cultevo
https://link.springer.com/article/10.1007/s10539-025-09982-4

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Zhao Mandi, Yifan Hou, Dieter Fox, Yashraj Narang, Ajay Mandlekar, Shuran Song
https://arxiv.org/abs/2505.24853

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
We study the problem of functional retargeting: learning dexterous manipulation policies to track object states from human hand-object demonstrations. We focus on long-horizon, bimanual tasks with articulated objects, which is challenging due to large action space, spatiotemporal discontinuities, and embodiment gap between human and robot hands. We propose DexMachina, a novel curriculum-based algorithm: the key idea is to use virtual object controllers with decaying strength: an object is first…

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…

This https://arxiv.org/abs/2501.02333 has been replaced.
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On The Causal Network Of Face-selective Regions In Human Brain During Movie Watching
Understanding the causal interactions in some brain tasks, such as face processing, remains a challenging and ambiguous process for researchers. In this study, we address this issue by employing a novel causal discovery method -Directed Acyclic Graphs via M-matrices for Acyclicity (DAGMA)- to investigate the causal structure of the brain's face-selective network and gain deeper insights into its mechanism. Using fMRI data of natural movie stimuli, we extract causal network of face-selective reg…

This https://arxiv.org/abs/2505.22688 has been replaced.
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Investigating the effectiveness of multimodal data in forecasting SARS-COV-2 case surges
The COVID-19 pandemic response relied heavily on statistical and machine learning models to predict key outcomes such as case prevalence and fatality rates. These predictions were instrumental in enabling timely public health interventions that helped break transmission cycles. While most existing models are grounded in traditional epidemiological data, the potential of alternative datasets, such as those derived from genomic information and human behavior, remains underexplored. In the current…

Object knowledge representation in the human visual cortex requires a connection with the language system https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003161 "Our experiments reveal the contribution of the vision-la…

Object knowledge representation in the human visual cortex requires a connection with the language system
This study shows that communication between the visual cortex and the brain language system is necessary for the representation of object knowledge in the visual cortex and for corresponding behaviors in humans. This highlights the significance of connections between sensory and language systems for object knowledge in the human brain.

New color just dropped https://www.livescience.com/health/neuroscience/scientists-hijacked-the-human-eye-to-get-it-to-see-a-brand-new-color-its-called-olo

When Brooke Nichols plugged in the data, she couldn’t comprehend what she was seeing.
The mathematician and professor of infectious diseases at Boston University had created a model to predict the human cost of the Department of Government Efficiency’s (Doge) USAid funding cuts.
As Elon Musk, the head of Doge, arrived at the White House on Friday afternoon
to be congratulated by President Trump for his work slashing the federal budget,
the number of deaths on Nichols’…

Doge cuts to USAid blamed for 300,000 deaths — most of them children
Elon Musk’s tenure running Trump’s Department of Government Efficiency has, according to the academic Brooke Nichols, caused thousands of ‘preventable deaths’

Exploring Societal Concerns and Perceptions of AI: A Thematic Analysis through the Lens of Problem-Seeking
Naomi Omeonga wa Kayembe
https://arxiv.org/abs/2505.23930

Exploring Societal Concerns and Perceptions of AI: A Thematic Analysis through the Lens of Problem-Seeking
This study introduces a novel conceptual framework distinguishing problem-seeking from problem-solving to clarify the unique features of human intelligence in contrast to AI. Problem-seeking refers to the embodied, emotionally grounded process by which humans identify and set goals, while problem-solving denotes the execution of strategies aimed at achieving such predefined objectives. The framework emphasizes that while AI excels at efficiency and optimization, it lacks the orientation derived…

What factors are increasing zoonosis emergence? (Diseases transmitted from animals to human)
#environment #forest #deforestation

Google’s AI Chief on the State of Artificial Intelligence (New York Times, 23 May 2025)
https://www.nytimes.com/2025/05/23/podcasts/google-ai-demis-hassabi…

Google DeepMind’s Demis Hassabis on AGI, Innovation and More
Demis Hassabis, the chief executive of Google DeepMind, says that “we’re quite close” to human-level artificial intelligence. After that, all bets are off.

MIRROR: Cognitive Inner Monologue Between Conversational Turns for Persistent Reflection and Reasoning in Conversational LLMs
Nicole Hsing
https://arxiv.org/abs/2506.00430

MIRROR: Cognitive Inner Monologue Between Conversational Turns for Persistent Reflection and Reasoning in Conversational LLMs
Human intelligence relies on inner monologue to process complex information through simultaneous reflection, memory retrieval, and response formulation. We introduce MIRROR (Modular Internal Reasoning, Reflection, Orchestration, and Response), a cognitive architecture that systematically implements these parallel reasoning capabilities in large language models. MIRROR operates as a unified system with two distinct functional layers: the Thinker and the Talker. The Thinker encompasses: (1) the I…

Snorkel AI, which pivoted from data labeling to building AI evaluation tools, raised a $100M Series D led by Addition at a $1.3B valuation, up from $1B in 2021 (Rashi Shrivastava/Forbes)
https://www.forbes.com/sites/rashishrivast…

Snorkel AI Raises $100 Million To Build Better Evaluators For AI Models
As it faces off against larger players, the data labelling startup is doubling down on using human experts to evaluate AI systems.

«AI systems are an attack on workers, climate goals, our information environment, and civil liberties. Rather than enhancing our human qualities, these systems degrade our social relations, and undermine our capacity for empathy and care.»
Nice writing by @…!
https://thedabbler.patatas.ca/pages/ai-is-dehumanization-technology.html

Semantics-Aware Human Motion Generation from Audio Instructions
Zi-An Wang, Shihao Zou, Shiyao Yu, Mingyuan Zhang, Chao Dong
https://arxiv.org/abs/2505.23465

Semantics-Aware Human Motion Generation from Audio Instructions
Recent advances in interactive technologies have highlighted the prominence of audio signals for semantic encoding. This paper explores a new task, where audio signals are used as conditioning inputs to generate motions that align with the semantics of the audio. Unlike text-based interactions, audio provides a more natural and intuitive communication method. However, existing methods typically focus on matching motions with music or speech rhythms, which often results in a weak connection betw…

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…

Alignment Revisited: Are Large Language Models Consistent in Stated and Revealed Preferences?
Zhuojun Gu, Quan Wang, Shuchu Han
https://arxiv.org/abs/2506.00751

Alignment Revisited: Are Large Language Models Consistent in Stated and Revealed Preferences?
Recent advances in Large Language Models (LLMs) highlight the need to align their behaviors with human values. A critical, yet understudied, issue is the potential divergence between an LLM's stated preferences (its reported alignment with general principles) and its revealed preferences (inferred from decisions in contextualized scenarios). Such deviations raise fundamental concerns for the interpretability, trustworthiness, reasoning transparency, and ethical deployment of LLMs, particularly …

A new COVID subvariant spreads rapidly as Trump pivots away from vaccines
A new, highly transmissible COVID subvariant has been detected in California
— heightening the risk of a potential summer wave
as recent moves by the Trump administration threaten to make vaccines harder to get,
and more expensive,
for many Americans,
some health experts warn.
Health and Human Services Secretary Robert F. Kennedy Jr.
announced this week that he was resci…

COVID variant NB.1.8.1 spreads as Trump pivots away from vaccines
A new, highly transmissible COVID subvariant has been detected in California — heightening the risk of a summer wave as recent moves by the Trump administration threaten to make vaccines harder to get, and more expensive, for many Americans, some health experts warn.

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education
Boning Zhao
https://arxiv.org/abs/2505.23631 https://

Human Empathy as Encoder: AI-Assisted Depression Assessment in Special Education
Assessing student depression in sensitive environments like special education is challenging. Standardized questionnaires may not fully reflect students' true situations. Furthermore, automated methods often falter with rich student narratives, lacking the crucial, individualized insights stemming from teachers' empathetic connections with students. Existing methods often fail to address this ambiguity or effectively integrate educator understanding. To address these limitations by fostering a …

RealDrive: Retrieval-Augmented Driving with Diffusion Models
Wenhao Ding, Sushant Veer, Yuxiao Chen, Yulong Cao, Chaowei Xiao, Marco Pavone
https://arxiv.org/abs/2505.24808

RealDrive: Retrieval-Augmented Driving with Diffusion Models
Learning-based planners generate natural human-like driving behaviors by learning to reason about nuanced interactions from data, overcoming the rigid behaviors that arise from rule-based planners. Nonetheless, data-driven approaches often struggle with rare, safety-critical scenarios and offer limited controllability over the generated trajectories. To address these challenges, we propose RealDrive, a Retrieval-Augmented Generation (RAG) framework that initializes a diffusion-based planning po…

Position: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence
Kordel K. France, Rohith Peddi, Nik Dennler, Ovidiu Daescu
https://arxiv.org/abs/2506.00398

Position: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence
Despite extraordinary progress in artificial intelligence (AI), modern systems remain incomplete representations of human cognition. Vision, audition, and language have received disproportionate attention due to well-defined benchmarks, standardized datasets, and consensus-driven scientific foundations. In contrast, olfaction - a high-bandwidth, evolutionarily critical sense - has been largely overlooked. This omission presents a foundational gap in the construction of truly embodied and ethica…

Humanoid World Models: Open World Foundation Models for Humanoid Robotics
Muhammad Qasim Ali, Aditya Sridhar, Shahbuland Matiana, Alex Wong, Mohammad Al-Sharman
https://arxiv.org/abs/2506.01182

Humanoid World Models: Open World Foundation Models for Humanoid Robotics
Humanoid robots have the potential to perform complex tasks in human centered environments but require robust predictive models to reason about the outcomes of their actions. We introduce Humanoid World Models (HWM) a family of lightweight open source video based models that forecast future egocentric observations conditioned on actions. We train two types of generative models Masked Transformers and FlowMatching on 100 hours of humanoid demonstrations. Additionally we explore architectural var…

Sleep Brain and Cardiac Activity Predict Cognitive Flexibility and Conceptual Reasoning Using Deep Learning
Boshra Khajehpiri, Eric Granger, Massimiliano de Zambotti, Fiona C. Baker, Mohamad Forouzanfar
https://arxiv.org/abs/2506.00279

Sleep Brain and Cardiac Activity Predict Cognitive Flexibility and Conceptual Reasoning Using Deep Learning
Despite extensive research on the relationship between sleep and cognition, the connection between sleep microstructure and human performance across specific cognitive domains remains underexplored. This study investigates whether deep learning models can predict executive functions, particularly cognitive adaptability and conceptual reasoning from physiological processes during a night's sleep. To address this, we introduce CogPSGFormer, a multi-scale convolutional-transformer model designed t…

STATE-NAV: Stability-Aware Traversability Estimation for Bipedal Navigation on Rough Terrain
Ziwon Yoon, Lawrence Y. Zhu, Lu Gan, Ye Zhao
https://arxiv.org/abs/2506.01046

STATE-NAV: Stability-Aware Traversability Estimation for Bipedal Navigation on Rough Terrain
Bipedal robots have advantages in maneuvering human-centered environments, but face greater failure risk compared to other stable mobile plarforms such as wheeled or quadrupedal robots. While learning-based traversability has been widely studied for these platforms, bipedal traversability has instead relied on manually designed rules with limited consideration of locomotion stability on rough terrain. In this work, we present the first learning-based traversability estimation and risk-sensitive…

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
Kourosh Shahnazari, Seyed Moein Ayyoubzadeh, Mohammadali Keshtparvar
https://arxiv.org/abs/2506.00328

BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies
The quest for interpretable reinforcement learning is a grand challenge for the deployment of autonomous decision-making systems in safety-critical applications. Modern deep reinforcement learning approaches, while powerful, tend to produce opaque policies that compromise verification, reduce transparency, and impede human oversight. To address this, we introduce BASIL (Best-Action Symbolic Interpretable Learning), a systematic approach for generating symbolic, rule-based policies via online ev…

DiG-Net: Enhancing Quality of Life through Hyper-Range Dynamic Gesture Recognition in Assistive Robotics
Eran Bamani Beeri, Eden Nissinman, Avishai Sintov
https://arxiv.org/abs/2505.24786

DiG-Net: Enhancing Quality of Life through Hyper-Range Dynamic Gesture Recognition in Assistive Robotics
Dynamic hand gestures play a pivotal role in assistive human-robot interaction (HRI), facilitating intuitive, non-verbal communication, particularly for individuals with mobility constraints or those operating robots remotely. Current gesture recognition methods are mostly limited to short-range interactions, reducing their utility in scenarios demanding robust assistive communication from afar. In this paper, we introduce a novel approach designed specifically for assistive robotics, enabling …

This https://arxiv.org/abs/2504.21841 has been replaced.
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Neuro-Symbolic Generation of Explanations for Robot Policies with Weighted Signal Temporal Logic
Neural network-based policies have demonstrated success in many robotic applications, but often lack human-explanability, which poses challenges in safety-critical deployments. To address this, we propose a neuro-symbolic explanation framework that generates a weighted signal temporal logic (wSTL) specification to describe a robot policy in a interpretable form. Existing methods typically produce explanations that are verbose and inconsistent, which hinders explainability, and loose, which do n…

This https://arxiv.org/abs/2505.12583 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics
Recent Foundation Model-enabled robotics (FMRs) display greatly improved general-purpose skills, enabling more adaptable automation than conventional robotics. Their ability to handle diverse tasks thus creates new opportunities to replace human labor. However, unlike general foundation models, FMRs interact with the physical world, where their actions directly affect the safety of humans and surrounding objects, requiring careful deployment and control. Based on this proposition, our survey co…

Conversational Alignment with Artificial Intelligence in Context
Rachel Katharine Sterken (University of Hong Kong), James Ravi Kirkpatrick (University of Oxford,Magdalen College, Oxford)
https://arxiv.org/abs/2505.22907

Conversational Alignment with Artificial Intelligence in Context
The development of sophisticated artificial intelligence (AI) conversational agents based on large language models raises important questions about the relationship between human norms, values, and practices and AI design and performance. This article explores what it means for AI agents to be conversationally aligned to human communicative norms and practices for handling context and common ground and proposes a new framework for evaluating developers' design choices. We begin by drawing on th…