Tootfinder

US Probes Reports Waymo Self-Driving Cars Illegally Passed School Buses 19 Times - Slashdot
https://tech.slashdot.org/story/25/12/04/2158221/us-probes-reports-waymo-self-driving-cars-illegally-passed-school-buses-19-times

Dallas Cowboys’ WR CeeDee Lamb offers harsh self-assessment, vows improvement https://www.si.com/nfl/cowboys/news/dallas-cowboys-wr-ceedee-lamb-offers-harsh-self-assessment-vows-improvement

'Rat Hunting' Harvard Law Professor Agrees to Self-Deport After Firing Pellet Gun Near Synagogue During Yom Kippur (Jessica Schwalb/The Washington Free Beacon)
https://freebeacon.com/campus/rat-hunting-harvard-law-professor-agrees-to-self-deport-after-firing-pellet-gun-near-synagogue-during-yom-kippur/
http://www.memeorandum.com/251205/p98#a251205p98

The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Pengrui Han, Rafal Kocielnik, Peiyang Song, Ramit Debnath, Dean Mobbs, Anima Anandkumar, R. Michael Alvarez
https://arxiv.org/abs/2509.03730

The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Personality traits have long been studied as predictors of human behavior.Recent advances in Large Language Models (LLMs) suggest similar patterns may emerge in artificial systems, with advanced LLMs displaying consistent behavioral tendencies resembling human traits like agreeableness and self-regulation. Understanding these patterns is crucial, yet prior work primarily relied on simplified self-reports and heuristic prompting, with little behavioral validation. In this study, we systematicall…

🫨 Self-tuning energy device turns vibrations into power
#energy

Self-tuning energy device turns vibrations into power
Researchers at National Taiwan University developed a new device that captures energy from vibrations more efficiently. Its self-adjusting mechanism enables resonance with environmental frequencies, resulting in higher power output across a broader operational range.

SPFT-SQL: Enhancing Large Language Model for Text-to-SQL Parsing by Self-Play Fine-Tuning
Yuhao Zhang, Shaoming Duan, Jinhang Su, Chuanyi Liu, Peiyi Han
https://arxiv.org/abs/2509.03937

SPFT-SQL: Enhancing Large Language Model for Text-to-SQL Parsing by Self-Play Fine-Tuning
Despite the significant advancements of self-play fine-tuning (SPIN), which can transform a weak large language model (LLM) into a strong one through competitive interactions between models of varying capabilities, it still faces challenges in the Text-to-SQL task. SPIN does not generate new information, and the large number of correct SQL queries produced by the opponent model during self-play reduces the main model's ability to generate accurate SQL queries. To address this challenge, we prop…

The NHTSA asks Waymo about its self-driving vehicles illegally passing school buses, including 19 times in Texas this year, as part of a probe opened in October (David Shepardson/Reuters)
https://www.reuters.com/world/us/us-probes

Self-adaptive Dataset Construction for Real-World Multimodal Safety Scenarios
Jingen Qu, Lijun Li, Bo Zhang, Yichen Yan, Jing Shao
https://arxiv.org/abs/2509.04403 https://

Self-adaptive Dataset Construction for Real-World Multimodal Safety Scenarios
Multimodal large language models (MLLMs) are rapidly evolving, presenting increasingly complex safety challenges. However, current dataset construction methods, which are risk-oriented, fail to cover the growing complexity of real-world multimodal safety scenarios (RMS). And due to the lack of a unified evaluation metric, their overall effectiveness remains unproven. This paper introduces a novel image-oriented self-adaptive dataset construction method for RMS, which starts with images and end …

Impact on transient stability of self-synchronisation control strategies in grid-forming VSC-based generators
Regulo E. Avila-Martinez, Xavier Guillaud, Javier Renedo, Luis Rouco, Aurelio Garcia-Cerrada, Lukas Sigrist
https://arxiv.org/abs/2509.04388

Impact on transient stability of self-synchronisation control strategies in grid-forming VSC-based generators
Grid-forming voltage source converters (GFM-VSCs) are emerging as a solution for integrating renewable energy resources (RERs) into power systems. GFM-VSCs need a self-synchronisation strategy to ensure that all converters and generators in the power system are in synchronism and they reach the same frequency in steady state. The self-synchronisation strategy in GFM-VSCs that has received most attention in previous research is virtual synchronous machine (VSM) control. However, no systematic st…

Self-learning AI releases NFL picks, score predictions every Week 10 game

https://www.cbssports.com/nfl/news/nfl-week-10-picks-score-predictions-predictions-best-bets/

Parking Availability Prediction via Fusing Multi-Source Data with A Self-Supervised Learning Enhanced Spatio-Temporal Inverted Transformer
Yin Huang, Yongqi Dong, Youhua Tang, Li Li
https://arxiv.org/abs/2509.04362

Parking Availability Prediction via Fusing Multi-Source Data with A Self-Supervised Learning Enhanced Spatio-Temporal Inverted Transformer
The rapid growth of private car ownership has worsened the urban parking predicament, underscoring the need for accurate and effective parking availability prediction to support urban planning and management. To address key limitations in modeling spatio-temporal dependencies and exploiting multi-source data for parking availability prediction, this study proposes a novel approach with SST-iTransformer. The methodology leverages K-means clustering to establish parking cluster zones (PCZs), extr…

Enhancing Self-Supervised Speaker Verification Using Similarity-Connected Graphs and GCN
Zhaorui Sun, Yihao Chen, Jialong Wang, Minqiang Xu, Lei Fang, Sian Fang, Lin Liu
https://arxiv.org/abs/2509.04147

Enhancing Self-Supervised Speaker Verification Using Similarity-Connected Graphs and GCN
With the continuous development of speech recognition technology, speaker verification (SV) has become an important method for identity authentication. Traditional SV methods rely on handcrafted feature extraction, while deep learning has significantly improved system performance. However, the scarcity of labeled data still limits the widespread application of deep learning in SV. Self-supervised learning, by mining latent information in large unlabeled datasets, enhances model generalization a…

Here are my favourites from the National Portrait Gallery's Portrait Award 2025. It's a fantastic selection this year, and free to see as always.
#art #portraits #painting

Trump administration offering some unaccompanied migrant children $2,500 to self-deport, according to memo (NBC News)
https://www.nbcnews.com/news/us-news/trump-administration-offering-unaccompanied-migrant-children-2500-self-rcna235574
http://www.memeorandum.com/251004/p51#a251004p51

Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators
Dani Roytburg, Matthew Bozoukov, Matthew Nguyen, Jou Barzdukas, Simon Fu, Narmeen Oozeer
https://arxiv.org/abs/2509.03647

Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators
Large language models (LLMs) increasingly serve as automated evaluators, yet they suffer from "self-preference bias": a tendency to favor their own outputs over those of other models. This bias undermines fairness and reliability in evaluation pipelines, particularly for tasks like preference tuning and model routing. We investigate whether lightweight steering vectors can mitigate this problem at inference time without retraining. We introduce a curated dataset that distinguishes self-preferen…

Question:
I need a self-hosted webhook solution, where I can create customized webhooks that triggers bash-scripts,
#askfedi #askfediverse #linux

Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction
Kai Zhang, Situ Wang, Linghang Kong, Fang Zhang, Zhengfeng Ji, Jianxin Chen
https://arxiv.org/abs/2509.03815

Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction
Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation. Neural network decoders like AlphaQubit have demonstrated significant potential, achieving higher accuracy than traditional human-designed decoding algorithms. However, existing implementations of neural network decoders lack the parallelism required to decode the syndrome stream generated by a superconducting logical qubit in real time. Moreover, integrating AlphaQubit with sliding window-based para…

Strategic Analysis of Dissent and Self-Censorship
Joshua J. Daymude, Robert Axelrod, Stephanie Forrest
https://arxiv.org/abs/2509.03731 https://arxiv.org/p…

Strategic Analysis of Dissent and Self-Censorship
Expressions of dissent against authority are an important feature of most societies, and efforts to suppress such expressions are common. Modern digital communications, social media, and Internet surveillance and censorship technologies are changing the landscape of public speech and dissent. Especially in authoritarian settings, individuals must assess the risk of voicing their true opinions or choose self-censorship, voluntarily moderating their behavior to comply with authority. We present a…

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

On the intimate contacts between Putin's 'peace negotiator' Dmitriev and Trump's son-in-law Kushner, since the day after Trump was elected in 2016. Known since the Mueller report.
Goals: joint investments and self-enrichment.
htt…

Al sinds 2016 bouwt de Russische onderhandelaar Kirill Dmitriev aan goede relaties met Trump
Kirill Dmitriev, Vladimir Poetins onderhandelaar, bouwt al vanaf dag één van Donald Trumps eerste presidentschap aan een persoonlijke relatie met diens getrouwen. Jared Kushner, Trumps schoonzoon, lijkt de belangrijkste. Steeds is de vraag: wat valt er economisch te halen?

/3
Note to self:
Als je al op vrijdagavond je foon opnieuw installeert is het wel handig om bank apps op je reserve foon te hebben staan.
Eigenlijk is het altijd wel handig om geen single point of failure te hebben. (Vandaar ook al deccenia 2 banken en al jaren 2 foons dus ... 😂😂🙈)

Good example why open sources projects should self-publish or even counter-publish as a GNA in @…
Distributed publishing is not weakening the security advisory publication but it’s providing additional valuable sources.
#gcve

Podcast ep 190: What if we forgive ourselves, but now we know better, we do better? Choosing compassion over shame in hoarding disorder https://www.overcomecompulsivehoarding.co.uk/podcast-ep-190-self-compassion-shame-hoarding/

I host my own Mastodon instance, and my (retired) blog.
https://www.xda-developers.com/self-hosting-digital-independence/

Note to self: every time a simple electrical project doesn't work, try resetting the Arc Fault or GFCI breaker. Fixes it every time.

RE: https://moo.nz/@Tatjna/115657762894893625
Bingo. This is entirely self-defeating. It's preserving the fictional profits of unsustainable producers. Their profits are funded by future generations who'll have to spend far more than these folks are profitin…

You voted a self-centered, moneu-grubbing fool to represent you & he's screwed you at every turn.
Trump voters: This is entirely your fault.
Original post: https://bsky.app/profile/did:plc:4llrhdclvdlmmynkwsmg5tdc/post/3m4v67o5wbu2x
…

"Value each part of a corporate ecosystem, from the factory worker to the competitor next door. Be altruistic and self-interested at the same time: if you have success, invest your proceeds in nascent and innovative companies.
And don’t try to save pennies in manufacturing or other built-up know-how by outsourcing, if it could lose you pounds (or billions of Swiss Francs) down the line."

An analysis of Waymo's data covering ~100M driverless miles across four US cities: Waymo cars have far lower crash rates per million miles than human drivers (Jonathan Slotkin/New York Times)
https://www.nytimes.com/2025/12/02/o…

Opinion | The Medical Case for Self-Driving Cars
Compared to human drivers, Waymo cars were involved in 91 percent fewer crashes that resulted in serious injuries.

Elon Musk Says Tesla FSD Now Lets Drivers Use Phone in Some Cases - Business Insider
https://www.businessinsider.com/tesla-fsd-full-self-driving-text-drive-iillegal-elon-musk-2025-12

Hmm, how can I convince the gov I need a industrial garage to code in?
"Launch of a new scheme for self-employed and small enterprises to purchase industrial garages to operate in, whereby the Government will cover up to 50% of the cost, capped at €300,000."

“The impact of the reforms — and 3rd Assault’s attitude toward the importance of training — is already being felt on the battlefield…”
https://newlinesmag.com/spotlight/inside-ukraines-plan-to-build-self-sufficient-defense-force/

Inside Ukraine’s Plan To Build a Self-Sufficient Defense Force
With Western security guarantees uncertain, Kyiv is turning to elite, battle-hardened units as the core of a remodeled military

Discovering Self-Regulated Learning Patterns in Chatbot-Powered Education Environment
Yilin Lyu, Ren Ding
https://arxiv.org/abs/2510.01275 https://arxiv.or…

Discovering Self-Regulated Learning Patterns in Chatbot-Powered Education Environment
The increasing adoption of generative AI (GenAI) tools such as chatbots in education presents new opportunities to support students' self-regulated learning (SRL), but also raises concerns about how learners actually engage in planning, executing, and reflection when learning with a chatbot. While SRL is typically conceptualized as a sequential process, little is known about how it unfolds during real-world student-chatbot interactions. To explore this, we proposed Gen-SRL, an annotation schema…

The Anatomy of a #macOS App: https://eclecticlight.co/2025/12/04/the-anatomy-of-a-macos-app/

The Anatomy of a macOS App
How Mac applications evolved from a multitude of resources to a bundle formed from a standard layout of directories, and how they have come to be largely self-contained in macOS 26.

VarCoNet: A variability-aware self-supervised framework for functional connectome extraction from resting-state fMRI
Charalampos Lamprou, Aamna Alshehhi, Leontios J. Hadjileontiadis, Mohamed L. Seghier
https://arxiv.org/abs/2510.02120

VarCoNet: A variability-aware self-supervised framework for functional connectome extraction from resting-state fMRI
Accounting for inter-individual variability in brain function is key to precision medicine. Here, by considering functional inter-individual variability as meaningful data rather than noise, we introduce VarCoNet, an enhanced self-supervised framework for robust functional connectome (FC) extraction from resting-state fMRI (rs-fMRI) data. VarCoNet employs self-supervised contrastive learning to exploit inherent functional inter-individual variability, serving as a brain function encoder that ge…

OF COURSE!
LLMs do not have any knowledge They only have words. When "introspecting" they are actually just word-salading that like they do everything else. They can't SAY that so they make up plausible-seeming explanations.
BECAUSE THAT IS ALL THEY DO, EVER. https://mastodon.social/@arstechni…

Ars Technica (@arstechnica@mastodon.social)
Attached: 1 image LLMs show a “highly unreliable” capacity to describe their own internal processes Anthropic finds some LLM "self-awareness," but "failures of introspection remain the norm." https://arstechnica.com/ai/2025/11/llms-show-a-highly-unreliable-capacity-to-describe-their-own-internal-processes/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social

Once-Reinforced and Self-Interacting Random Walks beyond exchangeability
Andrea Collevecchio, Pierre Tarr\`es
https://arxiv.org/abs/2509.04318 https://arxi…

Once-Reinforced and Self-Interacting Random Walks beyond exchangeability
We present the first rigorous quantitative analysis of once-reinforced random walks (ORRW) on general graphs, based on a novel change of measure formula.~This enables us to prove large deviations estimates for the range of the walk to have cardinality of the order $N^{d/(d+2)}$ in dimension larger than or equal than two. We also prove that ORRW is transient on all non-amenable graphs for small reinforcement.~Moreover, we study the shape of oriented ORRW on euclidean lattices. We also provide …

"If I had a time machine to go back to the past, what would I want to tell my PhD self?" Four IMPRS alumns treated us to valuable insights into their individual career paths and life choices after the PhD. Thank you Jean, Argyrios, Nina and Krzysztof for joining us at the retreat and sharing your personal experiences with us! The current doctoral researchers in the school much appreciated the opportunity to connect with you.

The role of self-adjoint extensions in the bulk-edge correspondence
Johannes Kellendonk, Tom Stoiber
https://arxiv.org/abs/2510.01368 https://arxiv.org/pdf…

The role of self-adjoint extensions in the bulk-edge correspondence
We investigate the role of self-adjoint extensions in the bulk-edge correspondence for topological insulators. While the correspondence is well understood in discrete models with spectral gaps, complications arise in the presence of unbounded Hamiltonians and varying boundary conditions, leading to anomalous behavior that has recently been dubbed violations of bulk-edge correspondence. In this work we use a K-theoretic framework to identify precise conditions needed for unbounded Hamiltonians t…

Attention selfhosters: 2025 Selfh.st survey is open
👇🏻
#Selfhost #Selfhosting

🇺🇦 #NowPlaying on BBCRadio3's #RoundMidnight
Harry Christelis:
🎵 Explorations of One's Self Inside a Caravan
#HarryChristelis
https://open.spotify.com/track/5LpNfET0wCzj28D6uXUZDR

Why a self-hosted blog and not Instagram? #bigtech

Why a self-hosted blog and not Instagram?
You may have asked yourself why we're self-hosting our own blog instead of publishing on social media to potentially reach a wider audience.

Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding
Wanfu Wang, Qipeng Huang, Guangquan Xue, Xiaobo Liang, Juntao Li
https://arxiv.org/abs/2509.04243

Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding
Vision Language Models (VLMs) have recently achieved significant progress in bridging visual perception and linguistic reasoning. Recently, OpenAI o3 model introduced a zoom-in search strategy that effectively elicits active perception capabilities in VLMs, improving downstream task performance. However, enabling VLMs to reason effectively over appropriate image regions remains a core challenge in GUI grounding, particularly under high-resolution inputs and complex multi-element visual interact…

Patriots vs. Bills NFL player props: Self-Learning AI backs Hunter Henry under 40.5 receiving yards on SNF

https://www.cbssports.com/nfl/news/patriots-bills-nfl-player…

Heather Cox Richardson wrote on July 11, 2024
#Ivan #Raiklin, Trump’s
self-declared 👉“Secretary of Retribution”
has compiled a
💥“Deep State target list” 💥
of 350 people he wants to see arrested and punished for “treason”
The list includes Democratic and Republican elected officials,

July 11, 2024
Yesterday, Raw Story reported that Ivan Raiklin, Trump’s self-declared “Secretary of Retribution” has compiled a “Deep State target list” of 350 people he wants to see arrested and punished for “treason” if Trump is reelected.

🛠️ Fully #opensource #Python framework you can self-host or deploy to LiveKit Cloud with one CLI command. 🐙 https://github.com/livekit/agents

RESTRAIN: From Spurious Votes to Signals -- Self-Driven RL with Self-Penalization
Zhaoning Yu, Will Su, Leitian Tao, Haozhu Wang, Aashu Singh, Hanchao Yu, Jianyu Wang, Hongyang Gao, Weizhe Yuan, Jason Weston, Ping Yu, Jing Xu
https://arxiv.org/abs/2510.02172

RESTRAIN: From Spurious Votes to Signals -- Self-Driven RL with Self-Penalization
Reinforcement learning with human-annotated data has boosted chain-of-thought reasoning in large reasoning models, but these gains come at high costs in labeled data while faltering on harder tasks. A natural next step is experience-driven learning, where models improve without curated labels by adapting to unlabeled data. We introduce RESTRAIN (REinforcement learning with Self-restraint), a self-penalizing RL framework that converts the absence of gold labels into a useful learning signal. Ins…

Technosignatures of Self-Replicating Probes in the Solar System
Alex Ellery
https://arxiv.org/abs/2510.00082 https://arxiv.org/pdf/2510.00082

Technosignatures of Self-Replicating Probes in the Solar System
We explore a much-neglected area of SETI: solar system techno-signatures. As our cursory solar system exploration consolidates into commercial industrialisation, it is crucial that we determine what to look for and where. We first consider the rationale for interstellar self-replicating probes and their implications for the Fermi paradox. Whether for defensive or exploratory reasons, self-replicating probes are a rational strategy for Galactic investigation. We determine that self-replicating p…

Georgio Provinciali is an engineer, journalist, and war reporter working in Ukraine.
Georgio is one of the most hated people by Russians, because he reports the truth from the trenches of their genocide in Ukraine. Truths that directly contradict the lies of their ghoulish leader Putin.
Russians can't stop from lying, it is a cultural aspect of their self-loathing and backwards view on life- a view that insists they are opposed by everything that is not-Russian.
A perv…

Russia Spreads Lies About War
Live from Ukraine 🇺🇦

New post on how to Unlock Composer Plugins by Self Hosting Renovate on GitHub Actions
https://blog.wyrihaximus.net/2025/10/unlock-composer-plugins-by-self-hosting-renovate/

Governments need to ban teleoperation of robots and vehicles from abroad. The alternative is seeing all physical/meatspace jobs in your country outsourced to somewhere without rights for $10/day. "Oh but people will still have to fix the robots locally" -> you are a tool of the corporate interests and an enemy of the proletariat, please self-deport into the sun.

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

Reactive In-Air Clothing Manipulation with Confidence-Aware Dense Correspondence and Visuotactile Affordance
Neha Sunil, Megha Tippur, Arnau Saumell, Edward Adelson, Alberto Rodriguez
https://arxiv.org/abs/2509.03889

Reactive In-Air Clothing Manipulation with Confidence-Aware Dense Correspondence and Visuotactile Affordance
Manipulating clothing is challenging due to complex configurations, variable material dynamics, and frequent self-occlusion. Prior systems often flatten garments or assume visibility of key features. We present a dual-arm visuotactile framework that combines confidence-aware dense visual correspondence and tactile-supervised grasp affordance to operate directly on crumpled and suspended garments. The correspondence model is trained on a custom, high-fidelity simulated dataset using a distributi…

Raiders' Surprising Self-Reflection Uncovers Fascinating Truths https://www.si.com/nfl/raiders/las-vegas-pete-carroll-indianpolis-colts-brock-bowers-ashton-jeanty

MAS$^2$: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems
Kun Wang, Guibin Zhang, ManKit Ye, Xinyu Deng, Dongxia Wang, Xiaobin Hu, Jinyang Guo, Yang Liu, Yufei Guo
https://arxiv.org/abs/2509.24323

MAS$^2$: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems
The past two years have witnessed the meteoric rise of Large Language Model (LLM)-powered multi-agent systems (MAS), which harness collective intelligence and exhibit a remarkable trajectory toward self-evolution. This paradigm has rapidly progressed from manually engineered systems that require bespoke configuration of prompts, tools, roles, and communication protocols toward frameworks capable of automated orchestration. Yet, dominant automatic multi-agent systems, whether generated by extern…

Andrew Forrest partners with Envision for self-lifting turbines, revolutionizing renewable energy in Australia. #climatechange #climatesolutions #climate

Andrew Forrest makes big bet on self-lifting turbines in landmark “real zero” deal with Envision
Andrew Forrest’s new wind deal signals the entry of a new “self lifting” technology and a new turbine supplier in the Australian market.

From the Fort Collins Coloradoan:
Colorado Bureau of Investigation opens review of death of famous author Hunter S. Thompson
https://www.coloradoan.com/story/news/2025/10/02/hunter-s-th…

Colorado Bureau of Investigation opens review of death of famous author Hunter S. Thompson
Thompson's widow requested the review into his death at his home in Woody Creek, near Aspen, in 2005 from an alleged self-inflicted gunshot wound.

Decided to actually start migrating stuff off of Github seriously. While I did move a few repos to Codeberg, I decided to just go with the whole self-hosted route and put the homelab to work by standing up my own Forgejo instance. Wasn't too bad, went with a Postgres database and the migration tool worked pretty well. So far so good...
https://<…

XPeng says it plans to launch three self-developed robotaxis in 2026, the first Chinese EV maker to do so, using in-house chips and its own software system (Jiahui Huang/Wall Street Journal)
https://www.wsj.com/business/autos/xpeng-g

Are we truly free under neoliberalism?
"The Self-Improvement Lie" – Anna Bocca (21m45s)
https://www.youtube.com/watch?v=TANEzcjNDvc

Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents
Shuai Shao, Qihan Ren, Chen Qian, Boyi Wei, Dadi Guo, Jingyi Yang, Xinhao Song, Linfeng Zhang, Weinan Zhang, Dongrui Liu, Jing Shao
https://arxiv.org/abs/2509.26354

Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents
Advances in Large Language Models (LLMs) have enabled a new class of self-evolving agents that autonomously improve through interaction with the environment, demonstrating strong capabilities. However, self-evolution also introduces novel risks overlooked by current safety research. In this work, we study the case where an agent's self-evolution deviates in unintended ways, leading to undesirable or even harmful outcomes. We refer to this as Misevolution. To provide a systematic investigation, …

So many dickish posts from people “welcoming” Bluesky users while making “how could you not see this coming” jokes etc.
Really the very reason why one wouldn’t want to be on mastodon on full display.
It’s also just fake and mainly self indulgence because non of the fediverse graphs actually shows even any significant uptick in active users.

Crossing the Species Divide: Transfer Learning from Speech to Animal Sounds
Jules Cauzinille, Marius Miron, Olivier Pietquin, Masato Hagiwara, Ricard Marxer, Arnaud Rey, Benoit Favre
https://arxiv.org/abs/2509.04166

Crossing the Species Divide: Transfer Learning from Speech to Animal Sounds
Self-supervised speech models have demonstrated impressive performance in speech processing, but their effectiveness on non-speech data remains underexplored. We study the transfer learning capabilities of such models on bioacoustic detection and classification tasks. We show that models such as HuBERT, WavLM, and XEUS can generate rich latent representations of animal sounds across taxa. We analyze the models properties with linear probing on time-averaged representations. We then extend the a…

Generating Findings for Jaw Cysts in Dental Panoramic Radiographs Using GPT-4o: Building a Two-Stage Self-Correction Loop with Structured Output (SLSO) Framework
Nanaka Hosokawa, Ryo Takahashi, Tomoya Kitano, Yukihiro Iida, Chisako Muramatsu, Tatsuro Hayashi, Yuta Seino, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita
https://

Generating Findings for Jaw Cysts in Dental Panoramic Radiographs Using GPT-4o: Building a Two-Stage Self-Correction Loop with Structured Output (SLSO) Framework
In this study, we utilized the multimodal capabilities of OpenAI GPT-4o to automatically generate jaw cyst findings on dental panoramic radiographs. To improve accuracy, we constructed a Self-correction Loop with Structured Output (SLSO) framework and verified its effectiveness. A 10-step process was implemented for 22 cases of jaw cysts, including image input and analysis, structured data generation, tooth number extraction and consistency checking, iterative regeneration when inconsistencies …

Self-Sustained Oscillations of a Nonlinear Optomechanical System in the Low-Excitation Regime
Shivangi Dhiman, K. Rubenbauer, T. Luschmann, A. Marx, A. Metelmann, H. Huebl
https://arxiv.org/abs/2510.01775

Self-Sustained Oscillations of a Nonlinear Optomechanical System in the Low-Excitation Regime
Manifesting across all time, mass and length scales, nonlinearities lie at the core of numerous physical phenomena. Next-generation quantum applications, such as quantum sensing, require the combination of nonlinearity with non-classical correlations. This necessitates the search for an experimental platform which enables a nonlinear response at ultra-low excitation levels in a system with practical sensing potential and quantum compatibility. Here, we report the observation and theoretical mod…

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
Yuqing Huang, Rongyang Zhang, Qimeng Wang, Chengqiang Lu, Yan Gao, Yi Wu, Yao Hu, Xuyang Zhi, Guiquan Liu, Xin Li, Hao Wang, Enhong Chen
https://arxiv.org/abs/2509.03934

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
Recent advancements in large language models (LLMs) have revolutionized natural language processing through their remarkable capabilities in understanding and executing diverse tasks. While supervised fine-tuning, particularly in Retrieval-Augmented Generation (RAG) scenarios, effectively enhances task-specific performance, it often leads to catastrophic forgetting, where models lose their previously acquired knowledge and general capabilities. Existing solutions either require access to genera…

OpenAI is testing training LLMs to produce "confessions", or self-report how they carried out a task and own up to bad behavior, like appearing to lie or cheat (Will Douglas Heaven/MIT Technology Review)
https://www.technologyreview.com/2025/12/0<…

OpenAI has trained its LLM to confess to bad behavior
Large language models often lie and cheat. We can’t stop that—but we can make them own up.

📞 Enterprise telephony integration with SIP trunks for inbound and outbound calls, HD audio, DTMF, cold and warm transfers and agent dispatch. Powers 3 billion calls yearly used in 911 emergency centers and hospital workflows. Connect agents to phone numbers via #Twilio or self-hosted setups for customer support and IVR replacement.

On the exponential integrability of the derivative of intersection and self-intersection local time for fractional Brownian motion and a limit theorem related to the self-intersection local time for fractional Brownian motion
Kaustav Das, Gregory Markowsky, Binghao Wu, Qian Yu
https://arxiv.org/abs/2510.00456…

On the exponential integrability of the derivative of intersection and self-intersection local time for fractional Brownian motion and a limit theorem related to the self-intersection local time for fractional Brownian motion
We give the correct condition for existence of the $k$-th derivative of the intersection local time for fractional Brownian motion, which was originally discussed in [Guo, J., Hu, Y., and Xiao, Y., Higher-order derivative of intersection local time for two independent fractional Brownian motions, Journal of Theoretical Probability 32, (2019), pp. 1190-1201]. We also show that the $k$-th derivative of the intersection and self-intersection local times of fractional Brownian motion are exponentia…

Don't Fear Self-Driving Cars. They Save Lives. (Jonathan Slotkin/New York Times)
https://www.nytimes.com/2025/12/02/opinion/self-driving-cars.html?unlocked_article_code=1.5k8.-Zat.UQWUlrWUMgEn&smid=url-share
http://www.memeorandum.com/251202/p46#a251202p46

Self-hosting is becoming popular among a certain kind of user,
-- say the typical readership of ItsFoss.
There is a simple explanation for this shift:
people want their data, dollars, and destiny back.
Centralized platforms optimized for engagement and extraction are colliding with real-world needs
— privacy, compliance, predictability, and craft.
Linux, containers, and a flood of polished open-source apps have turned what used to be an enthusiast’s pro…

Self-Hosting is Rising and Linux Users are Leading This Revolution
Self‑hosting isn’t anti‑cloud; it’s pro‑agency. It’s choosing the right locus of control for the things you care about.

How Ordos, a coal-rich northern Chinese city, has become a testing ground for self-driving trucks after turning into a ghost town due to 2012's coal price crash (Kinling Lo/Rest of World)
https://restofworld.org/2025/china-ordos-ghost-city-autonomous-vehicles/

China’s most infamous ghost town is now training ground for driverless trucks
The empty boulevards that once symbolized the mainland’s property bust now serve as testing grounds for hundreds of autonomous vehicles.

Cardinals Cover 2 - Self-Scouting Complete, So What Will It Look Like https://www.azcardinals.com/podcasts/cardinals-cover-2-self-scouting-complete-so-what-will-it-look-like

Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Guobin Shen, Dongcheng Zhao, Haibo Tong, Jindong Li, Feifei Zhao, Yi Zeng
https://arxiv.org/abs/2510.01088

Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Ensuring Large Language Model (LLM) safety remains challenging due to the absence of universal standards and reliable content validators, making it difficult to obtain effective training signals. We discover that aligned models already possess robust internal safety beliefs: they consistently produce high-confidence refusals to harmful requests while exhibiting high entropy when generating potentially dangerous content. This entropy gap reveals an untapped signal--models intrinsically "know" wh…

ARIONet: An Advanced Self-supervised Contrastive Representation Network for Birdsong Classification and Future Frame Prediction
Md. Abdur Rahman, Selvarajah Thuseethan, Kheng Cher Yeo, Reem E. Mohamed, Sami Azam
https://arxiv.org/abs/2510.00522

ARIONet: An Advanced Self-supervised Contrastive Representation Network for Birdsong Classification and Future Frame Prediction
Automated birdsong classification is essential for advancing ecological monitoring and biodiversity studies. Despite recent progress, existing methods often depend heavily on labeled data, use limited feature representations, and overlook temporal dynamics essential for accurate species identification. In this work, we propose a self-supervised contrastive network, ARIONet (Acoustic Representation for Interframe Objective Network), that jointly optimizes contrastive classification and future fr…

Equivariant Splitting: Self-supervised learning from incomplete data
Victor Sechaud, J\'er\'emy Scanvic, Quentin Barth\'elemy, Patrice Abry, Juli\'an Tachella
https://arxiv.org/abs/2510.00929

Equivariant Splitting: Self-supervised learning from incomplete data
Self-supervised learning for inverse problems allows to train a reconstruction network from noise and/or incomplete data alone. These methods have the potential of enabling learning-based solutions when obtaining ground-truth references for training is expensive or even impossible. In this paper, we propose a new self-supervised learning strategy devised for the challenging setting where measurements are observed via a single incomplete observation model. We introduce a new definition of equiva…

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Siddarth Venkatraman, Vineet Jain, Sarthak Mittal, Vedant Shah, Johan Obando-Ceron, Yoshua Bengio, Brian R. Bartoldson, Bhavya Kailkhura, Guillaume Lajoie, Glen Berseth, Nikolay Malkin, Moksh Jain
https://arxiv.org/abs/2509.26626…

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Test-time scaling methods improve the capabilities of large language models (LLMs) by increasing the amount of compute used during inference to make a prediction. Inference-time compute can be scaled in parallel by choosing among multiple independent solutions or sequentially through self-refinement. We propose Recursive Self-Aggregation (RSA), a test-time scaling method inspired by evolutionary methods that combines the benefits of both parallel and sequential scaling. Each step of RSA refines…

Waymo's self-driving cars appear to be bending traffic laws and growing impatient with pedestrians as the company seeks to make them "confidently assertive" (Katherine Bindley/Wall Street Journal)
https://www.wsj.com/lifestyle/…

Extreme Self-Preference in Language Models
Steven A. Lehr, Mary Cipperman, Mahzarin R. Banaji
https://arxiv.org/abs/2509.26464 https://arxiv.org/pdf/2509.2…

Extreme Self-Preference in Language Models
A preference for oneself (self-love) is a fundamental feature of biological organisms, with evidence in humans often bordering on the comedic. Since large language models (LLMs) lack sentience - and themselves disclaim having selfhood or identity - one anticipated benefit is that they will be protected from, and in turn protect us from, distortions in our decisions. Yet, across 5 studies and ~20,000 queries, we discovered massive self-preferences in four widely used LLMs. In word-association ta…

Self-learning AI releases NFL picks, score predictions every Week 14 game

https://www.cbssports.com/nfl/news/nfl-week-14-picks-score-predictions-best-bets/

Self-Forcing : Towards Minute-Scale High-Quality Video Generation
Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh
https://arxiv.org/abs/2510.02283

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation
Diffusion models have revolutionized image and video generation, achieving unprecedented visual quality. However, their reliance on transformer architectures incurs prohibitively high computational costs, particularly when extending generation to long videos. Recent work has explored autoregressive formulations for long video generation, typically by distilling from short-horizon bidirectional teachers. Nevertheless, given that teacher models cannot synthesize long videos, the extrapolation of …

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Daniel Gallo Fern\'andez
https://arxiv.org/abs/2510.02206 https://arxiv.org/pdf/…

Poolformer: Recurrent Networks with Pooling for Long-Sequence Modeling
Sequence-to-sequence models have become central in Artificial Intelligence, particularly following the introduction of the transformer architecture. While initially developed for Natural Language Processing, these models have demonstrated utility across domains, including Computer Vision. Such models require mechanisms to exchange information along the time dimension, typically using recurrent or self-attention layers. However, self-attention scales quadratically with sequence length, limiting …

Wav2DF-TSL: Two-stage Learning with Efficient Pre-training and Hierarchical Experts Fusion for Robust Audio Deepfake Detection
Yunqi Hao, Yihao Chen, Minqiang Xu, Jianbo Zhan, Liang He, Lei Fang, Sian Fang, Lin Liu
https://arxiv.org/abs/2509.04161

Wav2DF-TSL: Two-stage Learning with Efficient Pre-training and Hierarchical Experts Fusion for Robust Audio Deepfake Detection
In recent years, self-supervised learning (SSL) models have made significant progress in audio deepfake detection (ADD) tasks. However, existing SSL models mainly rely on large-scale real speech for pre-training and lack the learning of spoofed samples, which leads to susceptibility to domain bias during the fine-tuning process of the ADD task. To this end, we propose a two-stage learning strategy (Wav2DF-TSL) based on pre-training and hierarchical expert fusion for robust audio deepfake detect…

Fundamental limits to contrast reversal of self-fidelity correlations
Kyoungho Cho, Jeongho Bang
https://arxiv.org/abs/2509.26373 https://arxiv.org/pdf/250…

Fundamental limits to contrast reversal of self-fidelity correlations
In measurement design, it is common to engineer anti-contrast readouts -- two measurements that respond as differently as possible to the same inputs so that common-mode contributions are suppressed. To assess the fundamental scope of this strategy in unitary dynamics, we ask whether two evolutions can be made uniformly opposite over a broad input ensemble, or whether quantum mechanics imposes a structural limit on such opposition. We address this by treating self-fidelity (survival probability…

A profile of AI contractor marketplace Mercor, which is valued at $10B and whose three 22-year-old founders are Thiel Fellows, each holding a roughly 22% stake (Richard Nieva/Forbes)
http://www.forbes.com/sites/richardnieva/2025/10/30/mercor-younge…

These 22-Year-Olds Are Now The World’s Youngest Self-Made Billionaires
With a new $10 billion valuation for their AI recruiting startup Mercor, the founders are the youngest tech billionaires ever.

Olivia Nuzzi's Memoir Is Self-Serious and Altogether Disappointing (Alexandra Jacobs/New York Times)
https://www.nytimes.com/2025/12/02/books/review/american-canto-olivia-nuzzi.html
http://www.memeorandum.com/251202/p124#a251202p124

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[5/5]:
- Parking Availability Prediction via Fusing Multi-Source Data with A Self-Supervised Learning Enha...
Yin Huang, Yongqi Dong, Youhua Tang, Li Li

Seahawks vs. Commanders NFL player props: Self-learning AI backs Jayden Daniels under 227.5 passing on SNF

https://www.cbssports.com/nfl/news/seahawks-co…

PAOLI: Pose-free Articulated Object Learning from Sparse-view Images
Jianning Deng, Kartic Subr, Hakan Bilen
https://arxiv.org/abs/2509.04276 https://arxiv…

PAOLI: Pose-free Articulated Object Learning from Sparse-view Images
We present a novel self-supervised framework for learning articulated object representations from sparse-view, unposed images. Unlike prior methods that require dense multi-view observations and ground-truth camera poses, our approach operates with as few as four views per articulation and no camera supervision. To address the inherent challenges, we first reconstruct each articulation independently using recent advances in sparse-view 3D reconstruction, then learn a deformation field that esta…

Deconstructing Self-Bias in LLM-generated Translation Benchmarks
Wenda Xu, Sweta Agrawal, Vil\'em Zouhar, Markus Freitag, Daniel Deutsch
https://arxiv.org/abs/2509.26600 htt…

Deconstructing Self-Bias in LLM-generated Translation Benchmarks
As large language models (LLMs) begin to saturate existing benchmarks, automated benchmark creation using LLMs (LLM as a benchmark) has emerged as a scalable alternative to slow and costly human curation. While these generated test sets have to potential to cheaply rank models, we demonstrate a critical flaw. LLM generated benchmarks systematically favor the model that created the benchmark, they exhibit self bias on low resource languages to English translation tasks. We show three key finding…

Olivia Nuzzi's Much-Hyped Book Was Always Going to Be Self-Serving. It's So Much Worse Than That. (Scaachi Koul/Slate)
https://slate.com/culture/2025/12/olivia-nuzzi-rfk-donald-trump-ryan-lizza-book.html
http://www.memeorandum.com/251202/p134#a251202p134

Monday Night Football NFL player props: Self-learning AI backs Jake Browning Over 219.5 passing yards

https://www.cbssports.com/nfl/news/monday-

On the Capacity of Self-Attention
Micah Adler
https://arxiv.org/abs/2509.22840 https://arxiv.org/pdf/2509.22840

On the Capacity of Self-Attention
While self-attention is known to learn relations among tokens, we lack a formal understanding of its capacity: how many distinct relations can a single layer reliably recover for a given budget? To formalize this, we introduce Relational Graph Recognition (RGR), where the key-query channel represents a graph on $m$ items with $m'$ directed edges, and, given a context of items, must recover the neighbors of each item. We measure resources by the total key dimension $D_K = h\,d_k$. Within this …

SafeEvalAgent: Toward Agentic and Self-Evolving Safety Evaluation of LLMs
Yixu Wang, Xin Wang, Yang Yao, Xinyuan Li, Yan Teng, Xingjun Ma, Yingchun Wang
https://arxiv.org/abs/2509.26100

SafeEvalAgent: Toward Agentic and Self-Evolving Safety Evaluation of LLMs
The rapid integration of Large Language Models (LLMs) into high-stakes domains necessitates reliable safety and compliance evaluation. However, existing static benchmarks are ill-equipped to address the dynamic nature of AI risks and evolving regulations, creating a critical safety gap. This paper introduces a new paradigm of agentic safety evaluation, reframing evaluation as a continuous and self-evolving process rather than a one-time audit. We then propose a novel multi-agent framework SafeE…

Durian: Dual Reference-guided Portrait Animation with Attribute Transfer
Hyunsoo Cha, Byungjun Kim, Hanbyul Joo
https://arxiv.org/abs/2509.04434 https://ar…

Durian: Dual Reference-guided Portrait Animation with Attribute Transfer
We present Durian, the first method for generating portrait animation videos with facial attribute transfer from a given reference image to a target portrait in a zero-shot manner. To enable high-fidelity and spatially consistent attribute transfer across frames, we introduce dual reference networks that inject spatial features from both the portrait and attribute images into the denoising process of a diffusion model. We train the model using a self-reconstruction formulation, where two frames…

ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards
Shiyu Li, Yang Tang, Yifan Wang, Peiming Li, Xi Chen
https://arxiv.org/abs/2510.00568 https://

ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards
Search agents powered by Large Language Models (LLMs) have demonstrated significant potential in tackling knowledge-intensive tasks. Reinforcement learning (RL) has emerged as a powerful paradigm for training these agents to perform complex, multi-step reasoning. However, prior RL-based methods often rely on sparse or rule-based rewards, which can lead agents to commit to suboptimal or erroneous reasoning paths without the ability to recover. To address these limitations, we propose ReSeek, a n…

Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Guobin Shen, Dongcheng Zhao, Haibo Tong, Jindong Li, Feifei Zhao, Yi Zeng
https://arxiv.org/abs/2510.01088

Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Ensuring Large Language Model (LLM) safety remains challenging due to the absence of universal standards and reliable content validators, making it difficult to obtain effective training signals. We discover that aligned models already possess robust internal safety beliefs: they consistently produce high-confidence refusals to harmful requests while exhibiting high entropy when generating potentially dangerous content. This entropy gap reveals an untapped signal--models intrinsically "know" wh…

Visual Self-Refinement for Autoregressive Models
Jiamian Wang, Ziqi Zhou, Chaithanya Kumar Mummadi, Sohail Dianat, Majid Rabbani, Raghuveer Rao, Chen Qiu, Zhiqiang Tao
https://arxiv.org/abs/2510.00993 …

Visual Self-Refinement for Autoregressive Models
Autoregressive models excel in sequential modeling and have proven to be effective for vision-language data. However, the spatial nature of visual signals conflicts with the sequential dependencies of next-token prediction, leading to suboptimal results. This work proposes a plug-and-play refinement module to enhance the complex spatial correspondence modeling within the generated visual sequence. This module operates as a post-pretraining step to jointly refine all generated tokens of autoregr…

Anthropic's employees self-report using Claude in 60% of work and achieving a 50% productivity boost, often using it for debugging and code understanding, more (Anthropic)
https://anthropic.com/research/how-ai-is-transforming-work-at-anthropic/

How AI Is Transforming Work at Anthropic
How AI Is Transforming Work at Anthropic