@Techmeme@techhub.socialQ&A with Skild AI CEO Deepak Pathak on building a general-purpose brain for robots, standing out among big tech's robotics efforts, the path to AGI, and more (Alex Heath/Sources)
https://sources.news/p/skild-ai-ceo-robotics-brain-davos
@seeingwithsound@mas.to#Ultrasound gives the brain a nudge in the right direction https://www.ru.nl/en/research/research-news/ultrasound-gives-the-brain-a-nudge-in-the-right-d…
@heiseonline@social.heise.deMeta FAIR: KI-Zwilling für menschliche Neuronen
TRImodal Brain Encoder in zweiter Version veröffentlicht. Meta FAIR kann damit vorhersagen, wie das menschliche Gehirn reagiert.
https://www.heis…
@Speckdaene@nrw.social#Birds #birdwatching The reason for superiority: https://neurosciencenews.com/birdwatch
@netzschleuder@social.skewed.defly_larva: Drosophila larva brain (2023)
A complete synaptic map of the brain connectome of the larva of the fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using three-dimensional electron microscopy–based reconstruction. Node metadata include the neuron hempisphere, hemispherical homologue, cell type, annotations, and inferred cluster. Edge metadata include the type of interaction (`'aa'`,…
@MolemanPeter@neuromatch.socialThx Paul for a very informative and inspired Brain Inspired.
#neuroscience
@UP8@mastodon.social💡 Our brains may learn more from rare events than from repetition
#brain
@seeingwithsound@mas.toSeeing with the Brain (not the eyes) #LGN (lateral geniculate nucleus) over visual cortex for a visual prosthesis.
@netzschleuder@social.skewed.debudapest_connectome: Budapest Reference Connectome 3.0
A parameterizable consensus brain graph, derived from connectomes of 477 people, each computed from MRI datasets of the Human Connectome Project. Nodes are brain regions, and edges are weighted by the number of "tracks" that run between two nodes, as well as fiber length, fractional anisotropy and the number of occurrences in each of the 477 individuals.
This network has 1015 nodes and 63448 edges.
Tags: Biolo…
@azonenberg@ioc.exchangeSomebody send help i just looked up at some elongated fuzzy clouds and my brain went "wow i need to tweak the stigmators"
@memeorandum@universeodon.comLeader of Columbia Brain Institute Quits Over Friendship With Epstein (Sharon Otterman/New York Times)
https://www.nytimes.com/2026/02/25/nyregion/columbia-nobel-winner-epstein-resigns.html
http://www.memeorandum.com/260225/p42#a260225p42
@cdarwin@c.imIf you’ve never been into exercise or considered yourself “a gym person,” the idea of starting exercise in midlife can feel daunting, or even futile.
But here’s the good news:
from a scientific standpoint, your 40s may be one of the most powerful times to get started.
When it comes to bone, muscle, metabolism, heart health and even brain function, it is never too late to start exercising.
In fact, your body is remarkably responsive to change at this stage of life, and y…
@ErikUden@mastodon.deFor those who have been hearing of a Fly Brain being uploaded, the work you've been hearing of is impressive, yet as always the pop science media has warped what happened a bit:
„The Fly Brain Breakthrough Is Real. The “First Brain Upload” Narrative Is Not.”
https://…
@fanf@mendeddrum.orgRE: https://mastodon.xyz/@xkcd/116134642695834637
why does the compsci have a woolly hat? don’t they need a brain heatsink?
when i go out cycling in wintry subzero weather, i wear a fleecy band that stops my ears from getting frostbite, but still allows my…
@digitalnaiv@mastodon.socialDein KI-Kollege schläft nie 🧛 Du schon. Prompt schreiben. Output prüfen. Korrigieren. Neu prompten. Repeat. Das ist kein Workflow – das ist Erschöpfung. 14 % der KI-Nutzer berichten von Brain Fry. Marketer ganz vorne. Die KI setzt keine Grenzen. Das musst du tun.
#60Sekunden #KI
@davej@dice.campOf course #GraceTame’s difficult.
She’s a tireless campaigner for women and other overlooked and marginalised people. Were she meek and pliant, she’d be ignored; being difficult’s the only way to get her point across.
Our political class—Albo included—is too intransigent and dismissive and self-absorbed. We need more difficult women like Tame to puncture the Bubble and prod them to gover…
@grumpybozo@toad.socialRE: https://mastodon.social/@arstechnica/116132930980342790
It’s gonna be so funny when it turns out that Alzheimer’s is a post-viral syndrome of Varicella (brain Shingles!) and we turn out to have cured it inadvertently in recent decades by developing…
@Dragofix@veganism.socialE-waste chemicals are appearing in dolphins and porpoises #environment
@Techpizzamondays@social.linux.pizzaIs brain rot real? Why don’t you read a paper about it and join us this upcoming Monday at Victory Cafe, 440 Booor St. W. here in Toronto for the monthly @… edition, where we will discuss it? The Luma listing has a link to the paper: https://
@arXiv_csLG_bot@mastoxiv.pagePIME: Prototype-based Interpretable MCTS-Enhanced Brain Network Analysis for Disorder Diagnosis
Kunyu Zhang, Yanwu Yang, Jing Zhang, Xiangjie Shi, Shujian Yu
https://arxiv.org/abs/2602.21046 https://arxiv.org/pdf/2602.21046 https://arxiv.org/html/2602.21046
arXiv:2602.21046v1 Announce Type: new
Abstract: Recent deep learning methods for fMRI-based diagnosis have achieved promising accuracy by modeling functional connectivity networks. However, standard approaches often struggle with noisy interactions, and conventional post-hoc attribution methods may lack reliability, potentially highlighting dataset-specific artifacts. To address these challenges, we introduce PIME, an interpretable framework that bridges intrinsic interpretability with minimal-sufficient subgraph optimization by integrating prototype-based classification and consistency training with structural perturbations during learning. This encourages a structured latent space and enables Monte Carlo Tree Search (MCTS) under a prototype-consistent objective to extract compact minimal-sufficient explanatory subgraphs post-training. Experiments on three benchmark fMRI datasets demonstrate that PIME achieves state-of-the-art performance. Furthermore, by constraining the search space via learned prototypes, PIME identifies critical brain regions that are consistent with established neuroimaging findings. Stability analysis shows 90% reproducibility and consistent explanations across atlases.
toXiv_bot_toot
@thomasfuchs@hachyderm.io"We're just going to run a physical simulation of a human brain to achieve AGI"
"Won't the brain die instantly if it's without a body and oxygen supply etc?"
"Well, we'll just also simulate a body."
"Won't the body die instantly if it's in a vacuum?
"Fine, we'll just simulate an atmosphere too."
"Won't the body die if it's without food and light and gravity and stimulation?"
"Fine, we'll just simulate all the physical processes on the Earth."
"Won't the Earth just freeze instantly without the Sun being there?"
"Fine, we'll just simulate the sun, too."
"Will the solar system work properly if there's only the sun? What about gravitational influences of other mass in the galaxy, what about cosmic rays?"
"Fine, we'll just simulate the whole universe, too."
@ripienaar@devco.socialObsidian but free and with native MCP Server. Not tried but would be glad to be rid of obsidian
https://tolaria.md
@chiraag@mastodon.online @seeingwithsound@mas.toBrain implants: What's standing in the way of pivotal trials, FDA approval #BCI
@benb@osintua.eu“Brain Drain” or Temporary Wartime Realities? How the Number and Quality of Applicants to Ukrainian Higher Education Institutions Have Changed Since the Start of the Full-Scale Invasion: https://benborges.xyz/2026/02/19/brain-drain-or-temporary-wartime.html
@cdarwin@c.imSouth Carolina doesn’t require hospitals to report when they admit patients with measles-related illnesses.
Available data shows that only 2% of the state’s measles cases have resulted in hospitalizations. Some infectious disease experts fear significant underreporting.
Some doctors say they lack information about the severity of measles complications as it spreads around them.
@cheryanne@aus.socialGotta Go
A show for people who are juggling family, work, relationships, and the never-ending to-do list that lives rent-free in your brain...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/gotta-go/
@inthehands@hachyderm.ioI once again have the feeling that Randall Monroe can see directly into my brain (especially the mouseover text):
https://xkcd.com/3210/
@andres4ny@social.ridetrans.itNo! No no brain, no brain. no brain. Toot toot toot toot [unintelligible] like-like-like-like YeAH toot. boost. toot. boost. toot. toot toot toot toot like-like-like-like mastodon no brain. mastodon no brain. boost-toot-boost-toot. never! never! never! brain. boost toot boost toot. Never think!
https://
@netzschleuder@social.skewed.defly_hemibrain: Fly hemibrain (2020)
A synaptic map of the hemibrain connectome of fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using EM reconstruction techniques. Neurons are labeled by their type. Edges are annotated by the connection strength between the neurons.
This network has 21739 nodes and 4259624 edges.
Tags: Biological, Connectome, Weighted, Metadata
@hllizi@hespere.deI still remember the abject horror I felt when some "ConservaMom" on twotter back in the day 'pointed out' to those who wanted free and universal health care that a Ferrari would no more have value if everyone had one.
I don't know what exactly I replied, but it got me an instant block and I'd be ashamed of myself if it hadn't.
It really is a brain worm. But is there any hope for the affected? I think even in my most demented free-market-believer day…
@cowboys@darktundra.xyzCowboys front office explains their 'brain works' NFL Draft scouting outlook https://www.sportingnews.com/us/nfl/dallas-cowboys/news/cowboys-front-office-explains-brain-works-n…
@raysofred@discordian.social
@fortune@social.linux.pizzaNew Virus
There is a new virus going around called WORK. If you receive any sort
of WORK, whether via e-mail, Internet, or simply handed to you by a
colleague, do not open it. Those who have opened WORK have found that
their social life is deleted and their brain ceases to function
properly.
If you do encounter WORK via e-mail or are faced with any WORK at all,
purge the virus by sending an e-mail to your boss with the words 'This
is too much for…
@UP8@mastodon.social💢 MRI scans reveal how the brain processes toxic workplace abuse
#mri
@rigo@mamot.frIn der Juristerei wird das Aufkommen der LLMs begeistert gefeiert. Man versucht sich zu profilieren. Man ist vielleicht besorgt, dass die Stundensätze herunter gehen könnten. Aber sonst? Und dann diese Studie, die zeigt, dass bei Benutzung von LLMs die cognitive Kapazität und damit auch die Qualität dauernd nach unten zeigt. Kurz: Ein LLM-Anwalt bietet teure 0815-Soße, die man auch ohne Anwalt haben kann.
@cdarwin@c.imEPA Repeals Regulations for Mercury and Toxic Air Pollutants From Power Plants
Environmental and health groups said the change will make people sicker and supports a dying industry
https://www.thenewlede.org/2026/02/epa-rep…
@Techmeme@techhub.socialSources: Dell, Lenovo, and other PC makers are working with Nvidia on laptops using the Arm-based Nvidia-MediaTek system-on-a-chip, which could come in H1 2026 (Yang Jie/Wall Street Journal)
https://www.wsj.com/tech/nvidia-wants-to-be-the-brain-of-co…
@seeingwithsound@mas.toAstrocytes connect specific brain regions through plastic networks (in mice) https://www.nature.com/articles/s41586-026-10426-6 "communication between distant brain regions that is mediated by plastic networks of gap junction-coupled astrocytes";
@rberger@hachyderm.ioNext up, the Nurse Drain is just a part of the overall brain drain out of the US. Trump makes anyone who is skilled, has the opportunity and has half a brain to want to.
The Brain Drain into the USA was a key super power of the USA. Under Putin/Trump that is being destroyed. https://dmv.community/@AliceMarshall/116229967969444700
@thomasfuchs@hachyderm.ioOne of those things about claims of “AGI” is that to really build a human-like intelligence we’d have to simulate a human brain as whole because 1. it’s the only thing we know that produces human intelligence and 2. no one knows how it actually works.
Because of (2) it’s irrelevant what anyone says about LLMs or any other technology (with the exception of simulating a whole brain)—you can’t know if a technology is intelligent like a human because we don’t know what that means or how that works.
Fun thing, it turns out it’s impossible to simulate a whole brain with the resolution required (basically quantum physics level), and you’d have to emulate a chemical and physical environment for the brain as well (it will also need a body etc.).
You’d also have to simulate other humans with brains from which the brain can learn; but to simulate those you’d have simulate evolving humans from single-cell organisms first etc etc ad infinitum
@nohillside@smnn.chDad brains: How fatherhood rewires the male mind https://www.bbc.com/future/article/20260417-fatherhood-how-the-male-brain-and-body-prepare-for-childcare
@azonenberg@ioc.exchangeThe image just popped into my head of a PCBA manager in a Smokey Bear hat taking his blue-coated SMT technicians out for a morning run around the factory grounds singing cadence at them
I don't know but it's been said
Vintage solder's made of lead
Some say RoHS is a pain
But I kinda like my brain
Aoyue irons make me sad
But my Metcal ain't half bad
@qurlyjoe@mstdn.social#funFact
When you open your eyes to look at the world around you, what you “see” is an approximation that the collection of neurons and other cell types comprising your brain have learned to predict, based on the electrochemical signals—triggered by electromagnetic energy coursing through your external local environment—ricocheting around and through and amongst themselves (while they’re meanw…
@stefan@gardenstate.socialHow Hank Green Is Fighting Brain Rot by Slate
https://www.youtube.com/watch?v=GrDp8_Ao05U
@jake4480@c.imOne of the reasons I like music and movies so much is that they force my stupid fucking brain to think about something else for a few minutes
@Dragofix@veganism.socialMicroplastics may be quietly damaging your brain and fueling Alzheimer’s and Parkinson’s #health
@Techmeme@techhub.socialPhysical Intelligence says its new model, π0.7, can direct robots on tasks they weren't trained on, an "early sign" of generalization, surprising researchers (Connie Loizos/TechCrunch)
https://techcrunch.com/202…
@seeingwithsound@mas.toFortunately my brain is quite slow, so as long as I'm healthy I won't need an invasive BCI (brain implant) to output faster than I can type or talk (with or without AI), and I'll use a headset or smartglasses for AR/XR.
@chiraag@mastodon.onlineFascinating article in @…:
https://www.thetransmitter.org/defining-ce
@arXiv_csLG_bot@mastoxiv.pageHierarchic-EEG2Text: Assessing EEG-To-Text Decoding across Hierarchical Abstraction Levels
Anupam Sharma, Harish Katti, Prajwal Singh, Shanmuganathan Raman, Krishna Miyapuram
https://arxiv.org/abs/2602.20932 https://arxiv.org/pdf/2602.20932 https://arxiv.org/html/2602.20932
arXiv:2602.20932v1 Announce Type: new
Abstract: An electroencephalogram (EEG) records the spatially averaged electrical activity of neurons in the brain, measured from the human scalp. Prior studies have explored EEG-based classification of objects or concepts, often for passive viewing of briefly presented image or video stimuli, with limited classes. Because EEG exhibits a low signal-to-noise ratio, recognizing fine-grained representations across a large number of classes remains challenging; however, abstract-level object representations may exist. In this work, we investigate whether EEG captures object representations across multiple hierarchical levels, and propose episodic analysis, in which a Machine Learning (ML) model is evaluated across various, yet related, classification tasks (episodes). Unlike prior episodic EEG studies that rely on fixed or randomly sampled classes of equal cardinality, we adopt hierarchy-aware episode sampling using WordNet to generate episodes with variable classes of diverse hierarchy. We also present the largest episodic framework in the EEG domain for detecting observed text from EEG signals in the PEERS dataset, comprising $931538$ EEG samples under $1610$ object labels, acquired from $264$ human participants (subjects) performing controlled cognitive tasks, enabling the study of neural dynamics underlying perception, decision-making, and performance monitoring.
We examine how the semantic abstraction level affects classification performance across multiple learning techniques and architectures, providing a comprehensive analysis. The models tend to improve performance when the classification categories are drawn from higher levels of the hierarchy, suggesting sensitivity to abstraction. Our work highlights abstraction depth as an underexplored dimension of EEG decoding and motivates future research in this direction.
toXiv_bot_toot
@seeingwithsound@mas.toThus far about the only known advantage of a visual cortical prosthesis (brain implant for restoring vision) over visual-to-auditory sensory substitution is that you get to see blobs of light (phosphenes) if late-blind https://www.artificialvision.com/neuralink.htm
@UP8@mastodon.social💊 Faster to trials? Low-dose THC plus celecoxib improved cognition in Alzheimer's model mice
https://medicalxpress.com/news/2026-01-faster-trials-dose-thc-celecoxib.html
@seeingwithsound@mas.toHow psychedelics push your brain to dream while awake https://theconversation.com/how-psychedelics-push-your-brain-to-dream-while-awake-new-study-276708 Now how to nudge the brain of blind people to see through sound-guided mental image…
@cdarwin@c.imThe unusual electronic and optical properties of #perovskites have long been touted as useful for improving solar cells and television screens,
but these materials have never quite hit the big time.
Existing approaches have hoovered up all the investment and attention, and perovskites remain confined to specialist applications.
Now researchers at Empa, ETH Zurich and the Politecnico…
@heiseonline@social.heise.de @memeorandum@universeodon.comPresident, Extremely Normal Brain-Wise: Pope Weak On Crime, Also I'm Dr. Jesus Christ (Albert Burneko/Defector)
https://defector.com/president-extremely-normal-brain-wise-pope-weak-on-crime-also-im-dr-jesus-christ
http://www.memeorandum.com/260414/p150#a260414p150
@Techmeme@techhub.socialChinese brain-computer interface startup Gestala raised $21.6M co-led by Guosheng Capital and Dalton Venture at a $100M to $200M valuation, per CEO Phoenix Peng (Kate Park/TechCrunch)
https://techcrunch.com/2026/03/11/bci-startu…
@netzschleuder@social.skewed.defly_larva: Drosophila larva brain (2023)
A complete synaptic map of the brain connectome of the larva of the fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using three-dimensional electron microscopy–based reconstruction. Node metadata include the neuron hempisphere, hemispherical homologue, cell type, annotations, and inferred cluster. Edge metadata include the type of interaction (`'aa'`,…
@seeingwithsound@mas.to(LinkedIn) Romina Nejad, former clinical trials lead at Neuralink, has left Neuralink to join Salma Health as vice president clinical research https://www.linkedin.com/feed/update/urn:li:activity:7432841671396040704/
@arXiv_csLG_bot@mastoxiv.pageCrosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/3]:
- Functional Continuous Decomposition
Teymur Aghayev
https://arxiv.org/abs/2602.20857 https://mastoxiv.page/@arXiv_eessSP_bot/116130499236089653
- SpatiaLQA: A Benchmark for Evaluating Spatial Logical Reasoning in Vision-Language Models
Xie, Zhang, Shan, Zhu, Tang, Wei, Song, Wan, Song
https://arxiv.org/abs/2602.20901 https://mastoxiv.page/@arXiv_csCV_bot/116130845273808954
- Some Simple Economics of AGI
Christian Catalini, Xiang Hui, Jane Wu
https://arxiv.org/abs/2602.20946 https://mastoxiv.page/@arXiv_econGN_bot/116130470423837005
- Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures
Yubin Ge, Yongsong Huang, Xiaofeng Liu
https://arxiv.org/abs/2602.20994 https://mastoxiv.page/@arXiv_eessIV_bot/116130212832138624
- MIP Candy: A Modular PyTorch Framework for Medical Image Processing
Tianhao Fu, Yucheng Chen
https://arxiv.org/abs/2602.21033 https://mastoxiv.page/@arXiv_csCV_bot/116130864279556063
- Empirically Calibrated Conditional Independence Tests
Milleno Pan, Antoine de Mathelin, Wesley Tansey
https://arxiv.org/abs/2602.21036 https://mastoxiv.page/@arXiv_statME_bot/116130690605113562
- Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise
Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet
https://arxiv.org/abs/2602.21039 https://mastoxiv.page/@arXiv_statML_bot/116130572661848449
- Position-Aware Sequential Attention for Accurate Next Item Recommendations
Timur Nabiev, Evgeny Frolov
https://arxiv.org/abs/2602.21052 https://mastoxiv.page/@arXiv_csIR_bot/116130263323086316
- Motivation is Something You Need
Mehdi Acheli, Walid Gaaloul
https://arxiv.org/abs/2602.21064 https://mastoxiv.page/@arXiv_csAI_bot/116130680774678580
- An Enhanced Projection Pursuit Tree Classifier with Visual Methods for Assessing Algorithmic Impr...
Natalia da Silva, Dianne Cook, Eun-Kyung Lee
https://arxiv.org/abs/2602.21130 https://mastoxiv.page/@arXiv_statML_bot/116130610674573081
- Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
Kimon Fountoulakis, David Mart\'inez-Rubio
https://arxiv.org/abs/2602.21138 https://mastoxiv.page/@arXiv_mathOC_bot/116130547076073836
- LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Jiang, Yang, Nath, Parida, Kulkarni, Xu, Xu, Anwar, Roth, Linguraru
https://arxiv.org/abs/2602.21142 https://mastoxiv.page/@arXiv_csCV_bot/116130871488694585
- A Benchmark for Deep Information Synthesis
Debjit Paul, et al.
https://arxiv.org/abs/2602.21143 https://mastoxiv.page/@arXiv_csAI_bot/116130692571594706
- Scaling State-Space Models on Multiple GPUs with Tensor Parallelism
Anurag Dutt, Nimit Shah, Hazem Masarani, Anshul Gandhi
https://arxiv.org/abs/2602.21144 https://mastoxiv.page/@arXiv_csDC_bot/116130520888343997
- Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions
Mame Diarra Toure, David A. Stephens
https://arxiv.org/abs/2602.21160 https://mastoxiv.page/@arXiv_statML_bot/116130618512594211
- Aletheia tackles FirstProof autonomously
Tony Feng, et al.
https://arxiv.org/abs/2602.21201 https://mastoxiv.page/@arXiv_csAI_bot/116130705679345625
- Squint: Fast Visual Reinforcement Learning for Sim-to-Real Robotics
Abdulaziz Almuzairee, Henrik I. Christensen
https://arxiv.org/abs/2602.21203 https://mastoxiv.page/@arXiv_csRO_bot/116130765974498223
toXiv_bot_toot
@seeingwithsound@mas.toMarch 25, 2026: Conscious vision and its restoration in blindness https://neuronline.sfn.org/scientific-research/conscious-vision-and-its-restoration-in-blindness
@cdarwin@c.imThe “neural fingerprint” of psychedelics was spotted among hundreds of brain scans of people on LSD, psilocybin, DMT, mescaline and ayahuasca,
pointing to a shared impact on the brain’s behaviour.
The finding emerged from a major study that combined 11 brain imaging datasets from around the world
in an effort to build a reliable picture of how the substances temporarily rewire the brain.
Dr Danilo Bzdok and his colleagues analysed more than 500 brain scans from 267 p…
@UP8@mastodon.social🤯 The brain region associated with moral inconsistency
#brain
@seeingwithsound@mas.toWhat does Neuralink want — to help people with paralysis, or prepare for a war with AI? https://archive.ph/c96dg Conflicting rhetoric from Elon Musk's company impedes brain implants' ability to gain traction as medical devices, competitors say";
@Techmeme@techhub.socialA study of ~1,500 US workers finds AI use can reduce burnout but also cause "AI brain fry", a mental fatigue from using AI tools beyond one's cognitive capacity (Harvard Business Review)
https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry
@arXiv_csLG_bot@mastoxiv.pageReplaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/6]:
- Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints
Chuqin Geng, Li Zhang, Mark Zhang, Haolin Ye, Ziyu Zhao, Xujie Si
https://arxiv.org/abs/2602.16954 https://mastoxiv.page/@arXiv_csLG_bot/116102434757760085
- Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Fres...
Ziliang Zhao, et al.
https://arxiv.org/abs/2602.17050 https://mastoxiv.page/@arXiv_csLG_bot/116102517335590034
- MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sam...
Fu, Lin, Fang, Zheng, Hu, Shao, Qin, Pan, Zeng, Cai
https://arxiv.org/abs/2602.17550 https://mastoxiv.page/@arXiv_csLG_bot/116102581561441103
- A Theoretical Framework for Modular Learning of Robust Generative Models
Corinna Cortes, Mehryar Mohri, Yutao Zhong
https://arxiv.org/abs/2602.17554 https://mastoxiv.page/@arXiv_csLG_bot/116102582216715527
- Multi-Round Human-AI Collaboration with User-Specified Requirements
Sima Noorani, Shayan Kiyani, Hamed Hassani, George Pappas
https://arxiv.org/abs/2602.17646 https://mastoxiv.page/@arXiv_csLG_bot/116102592047544971
- NEXUS: A compact neural architecture for high-resolution spatiotemporal air quality forecasting i...
Rampunit Kumar, Aditya Maheshwari
https://arxiv.org/abs/2602.19654 https://mastoxiv.page/@arXiv_csLG_bot/116125610403473755
- Augmenting Lateral Thinking in Language Models with Humor and Riddle Data for the BRAINTEASER Task
Mina Ghashami, Soumya Smruti Mishra
https://arxiv.org/abs/2405.10385 https://mastoxiv.page/@arXiv_csCL_bot/112472190479013167
- Watermarking Language Models with Error Correcting Codes
Patrick Chao, Yan Sun, Edgar Dobriban, Hamed Hassani
https://arxiv.org/abs/2406.10281 https://mastoxiv.page/@arXiv_csCR_bot/112636307340218522
- Learning to Control Unknown Strongly Monotone Games
Siddharth Chandak, Ilai Bistritz, Nicholas Bambos
https://arxiv.org/abs/2407.00575 https://mastoxiv.page/@arXiv_csMA_bot/112715733875586837
- Classification and reconstruction for single-pixel imaging with classical and quantum neural netw...
Sofya Manko, Dmitry Frolovtsev
https://arxiv.org/abs/2407.12506 https://mastoxiv.page/@arXiv_quantph_bot/112806295477530195
- Statistical Inference for Temporal Difference Learning with Linear Function Approximation
Weichen Wu, Gen Li, Yuting Wei, Alessandro Rinaldo
https://arxiv.org/abs/2410.16106 https://mastoxiv.page/@arXiv_statML_bot/113350611306532443
- Big data approach to Kazhdan-Lusztig polynomials
Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz
https://arxiv.org/abs/2412.01283 https://mastoxiv.page/@arXiv_mathRT_bot/113587812663608119
- MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition
Mehran Shabanpour, Kasra Rad, Sadaf Khademi, Arash Mohammadi
https://arxiv.org/abs/2502.17457 https://mastoxiv.page/@arXiv_eessSP_bot/114069047434302054
- Tightening Optimality gap with confidence through conformal prediction
Miao Li, Michael Klamkin, Russell Bent, Pascal Van Hentenryck
https://arxiv.org/abs/2503.04071 https://mastoxiv.page/@arXiv_statML_bot/114120074927291283
- SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding
Juhyeon Park, Peter Yongho Kim, Jiook Cha, Shinjae Yoo, Taesup Moon
https://arxiv.org/abs/2503.06437 https://mastoxiv.page/@arXiv_csCV_bot/114142690988862508
- How much does context affect the accuracy of AI health advice?
Prashant Garg, Thiemo Fetzer
https://arxiv.org/abs/2504.18310 https://mastoxiv.page/@arXiv_econGN_bot/114414380916957986
- Reproducing and Improving CheXNet: Deep Learning for Chest X-ray Disease Classification
Daniel J. Strick, Carlos Garcia, Anthony Huang, Thomas Gardos
https://arxiv.org/abs/2505.06646 https://mastoxiv.page/@arXiv_eessIV_bot/114499319986528625
- Sharp Gaussian approximations for Decentralized Federated Learning
Soham Bonnerjee, Sayar Karmakar, Wei Biao Wu
https://arxiv.org/abs/2505.08125 https://mastoxiv.page/@arXiv_statML_bot/114505047719395949
- HoloLLM: Multisensory Foundation Model for Language-Grounded Human Sensing and Reasoning
Chuhao Zhou, Jianfei Yang
https://arxiv.org/abs/2505.17645 https://mastoxiv.page/@arXiv_csCV_bot/114572928659057348
- A Copula Based Supervised Filter for Feature Selection in Diabetes Risk Prediction Using Machine ...
Agnideep Aich, Md Monzur Murshed, Sameera Hewage, Amanda Mayeaux
https://arxiv.org/abs/2505.22554 https://mastoxiv.page/@arXiv_statML_bot/114589983451462525
- Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Florian F\"urrutter, Zohim Chandani, Ikko Hamamura, Hans J. Briegel, Gorka Mu\~noz-Gil
https://arxiv.org/abs/2506.01666 https://mastoxiv.page/@arXiv_quantph_bot/114618420761346125
toXiv_bot_toot
@UP8@mastodon.social⚡ Newly identified brain circuit and cells link prior experiences to appetite
#brain
@seeingwithsound@mas.toHow psychedelics push your brain to dream while awake https://medicalxpress.com/news/2026-03-psychedelics-brain.html "psychedelics make the brain more likely to 'see' images from memory rather than what's actually in front of it"; mental imagery
@netzschleuder@social.skewed.decintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted
@Techmeme@techhub.socialAn interview with Galen Buckwalter, a BCI recipient in a Caltech brain implant study, on his recent ability to use the implant to produce musical tones (Emily Mullin/Wired)
https://www.wired.com/story/meet-the-man-making-music-with-his-brain-implant/
@seeingwithsound@mas.toDesigning implants that don't scar the brain https://neurosciencenews.com/flexible-brain-implants-polyimide-biocompatibility-30538/ "Surprisingly, making probes 'ultra-thin' or allowing them to 'float' wirelessly didn't…
@seeingwithsound@mas.to"Why I don't think '#Neuralink' will ever be profitable" https://theneuroscienceofeverydaylife.substack.com/p/why-i-dont-think-neuralink-will-e…
@netzschleuder@social.skewed.debudapest_connectome: Budapest Reference Connectome 3.0
A parameterizable consensus brain graph, derived from connectomes of 477 people, each computed from MRI datasets of the Human Connectome Project. Nodes are brain regions, and edges are weighted by the number of "tracks" that run between two nodes, as well as fiber length, fractional anisotropy and the number of occurrences in each of the 477 individuals.
This network has 1015 nodes and 112890 edges.
Tags: Biol…
@seeingwithsound@mas.toArticle on the ReVision Implant brain implant originating from China (WeChat): WeChat #BCI #NeuroTech
@UP8@mastodon.social🎧 Earbuds can be used to monitor brain health
#sensors
@seeingwithsound@mas.toBrain-computer interfaces in healthcare: building the picks and shovels company while the giants fight over gold #BCI
@cdarwin@c.imIbogaine, a naturally occurring compound from a shrub native to Africa, is used to treat depression, anxiety, addiction, post-traumatic stress disorder and brain trauma.
Because it's illegal in the United States, Americans have been traveling to unregulated clinics, often in Mexico or the Caribbean, to take the drug.
Trump intends to sign the executive order as soon as this week, to allow its use in research
The administration doesn't plan to reclassify the drug …
@netzschleuder@social.skewed.defly_hemibrain: Fly hemibrain (2020)
A synaptic map of the hemibrain connectome of fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using EM reconstruction techniques. Neurons are labeled by their type. Edges are annotated by the connection strength between the neurons.
This network has 21739 nodes and 4259624 edges.
Tags: Biological, Connectome, Weighted, Metadata
@cdarwin@c.imThe devastating toll of Iran’s counterattack on U.S. service members after Donald Trump’s surprise strikes on Iran is even more severe than previously known.
A deadly attack that killed six U.S. service members has also left dozens of others suffering from traumatic brain injuries,
memory loss,
and other “urgent” health issues
at Landstuhl Regional Medical Center in Germany,
the largest U.S. military hospital abroad,
CBS News reported Wednesday.
As o…
@seeingwithsound@mas.toPostdoc position in brain plasticity (blindness/deafness) at Georgetown University, Washington DC #neuroscience
@netzschleuder@social.skewed.defly_larva: Drosophila larva brain (2023)
A complete synaptic map of the brain connectome of the larva of the fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using three-dimensional electron microscopy–based reconstruction. Node metadata include the neuron hempisphere, hemispherical homologue, cell type, annotations, and inferred cluster. Edge metadata include the type of interaction (`'aa'`,…
@seeingwithsound@mas.toNature: China approves brain chip to treat paralysis — a world first #Neuracle
@seeingwithsound@mas.toToward real-time fMRI? Exploring the sensitivity limits of neuronal current imaging with MRI and MEG in the human brain https://www.biorxiv.org/content/10.64898/2026.02.17.706369v1 Local magnetic field amplitudes of ∼0.07 nT still below detection threshold of 0.2 nT at 3T; …
@netzschleuder@social.skewed.debudapest_connectome: Budapest Reference Connectome 3.0
A parameterizable consensus brain graph, derived from connectomes of 477 people, each computed from MRI datasets of the Human Connectome Project. Nodes are brain regions, and edges are weighted by the number of "tracks" that run between two nodes, as well as fiber length, fractional anisotropy and the number of occurrences in each of the 477 individuals.
This network has 1015 nodes and 71604 edges.
Tags: Biolo…
@seeingwithsound@mas.toCrossmodal interaction of flashes and beeps across time and number follows Bayesian causal inference #SiFI
@seeingwithsound@mas.toMax Hodak's Science Corp. is preparing to place its first sensor in a human brain https://techcrunch.com/2026/04/14/max-hodaks-science-corp-is-preparing-to-place-its-first-sensor-in-a-human-brain/ biohybrid
@seeingwithsound@mas.toBrain-computer interfaces for vision recovery in precortical vision loss https://www.dovepress.com/brain-computer-interfaces-for-vision-recovery-in-precortical-vision-lo-peer-reviewed-fulltext-article-EB …
@seeingwithsound@mas.toParalyzed artist paints again: how one brain implant drives two pathways to recovery #NeuroXess #BCI
@seeingwithsound@mas.toSensory Substitution and Brain Plasticity Following Vision Loss (#SenSubMRI) https://ichgcp.net/amp/clinical-trials-registry/NCT07450677
@seeingwithsound@mas.toPaid research opportunity for blind participants. Must be blind from birth or infancy, and live within 50 miles of Washington DC https://docs.google.com/forms/d/e/1FAIpQLSccpnHzLPO1RlBQAa3UNGXJ9hjQn_jHRv5GvIb6hqM7-caj-A/viewform
@seeingwithsound@mas.toGarry Tan, VC and Y Combinator CEO: Brain computer interfaces are now giving sight back to the blind https://garryslist.org/posts/brain-computer-interfaces-are-now-giving-sight-back-to-the-blind by @…
@seeingwithsound@mas.toWhat it's like to have a brain implant for 5 years https://www.wired.com/story/synchron-brain-computer-interface-five-years-als/ (archived at
@seeingwithsound@mas.toPerception of brain-computer interface implantation surgery for motor, sensory, and autonomic restoration in spinal cord injury and stroke https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2026.1678175/full "first-ge…
@seeingwithsound@mas.toApplication of non-invasive brain-computer interfaces in spinal cord injury rehabilitation #BCI #NeuroTech
@seeingwithsound@mas.toVisual and tactile motion cues enhance the categorisation of novel object shapes #multisensory
@seeingwithsound@mas.toMovies reconstructed purely from mouse brain activity https://medicalxpress.com/news/2026-03-movies-reconstructed-purely-mouse-brain.html
Movie reconstruction from mouse visual cortex activity
@seeingwithsound@mas.toWould getting a Neuralink Blindsight brain implant for restoring vision be worth it? #BCI
@seeingwithsound@mas.toSimply sticking electrodes into primary visual cortex (V1) to evoke phosphenes ignores the feedback loops from higher visual areas back to V1. A Neuralink Blindsight brain implant will almost certainly perform very poorly. Engineering is one thing, biology/neuroscience another.
@seeingwithsound@mas.toPhD position at University of Glasgow on ultra-high field brain imaging of mental imagery and aphantasia https://www.findaphd.com/phds/project/fully-funded-phd-ultra-high-field-brain-imaging-of-imagery-and-aphantasia/?p196182…
