Tootfinder

Claude Code users, many on the $200-a-month Max plan, are unexpectedly facing restrictive usage limits; Anthropic says it's "working to resolve these issues" (Russell Brandom/TechCrunch)
https://techcrunch.com/2025/07/17/anth

Anthropic tightens usage limits for Claude Code – without telling users | TechCrunch
Claude Code users have been hit with unexpectedly restrictive usage limits. The problems, many of which have been aired on Claude Code’s GitHub page, seem to be concentrated among heavy users of the service, many of whom are on the $200-a-month Max plan. 

The inverse of the (alternating) infinite sum of the reciprocal of the weighted sum for generalized Fibonacci sub-sequences
Yongkang Wan, Zhonghao Liang, Qunying Liao
https://arxiv.org/abs/2509.14569

The inverse of the (alternating) infinite sum of the reciprocal of the weighted sum for generalized Fibonacci sub-sequences
In this paper, for the generalized Fibonacci sequence $\left\{W_n\left(a,b,p,q\right)\right\}$, by using elementary methods and techniques, we give the asymptotic estimation values of $\left(\sum\limits_{k=n}^{\infty}\frac{1}{\sum\limits_{i=0}^{t}s_{i}W_{mk+l_i}}\right)^{-1}$ and $\left(\sum\limits_{k=n}^{\infty}\frac{\left(-1\right)^k}{\sum\limits_{i=0}^{t}s_{i}W_{mk+l_i}}\right)^{-1}$, respectively. In particular, for some special $a,b,p,q,m,t,s_i$ and $l_i\left(0\leq i\leq t \right)$, Theore…

Maybe the model knows that there’s no org named “Antifa” that can be investigated and so gets a bit “psychotic” when forced to do so. https://mastodon.social/@arstechnica/115221901397524747

Ars Technica (@arstechnica@mastodon.social)
Attached: 1 image White House officials reportedly frustrated by Anthropic’s law enforcement AI limits Officials say Claude chatbot usage policies block FBI, Secret Service contractors' work. https://arstechnica.com/ai/2025/09/white-house-officials-reportedly-frustrated-by-anthropics-law-enforcement-ai-limits/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social

Magnetic-Field and Temperature Limits of a Kinetic-Inductance Traveling-Wave Parametric Amplifier
Lucas M. Janssen, Farzad Faramarzi, Henry G. LeDuc, Sahil Patel, Gianluigi Catelani, Peter K. Day, Yoichi Ando, Christian Dickel
https://arxiv.org/abs/2509.15043

Magnetic-Field and Temperature Limits of a Kinetic-Inductance Traveling-Wave Parametric Amplifier
Kinetic-inductance traveling-wave parametric amplifiers (KI-TWPAs) offer broadband near-quantum-limited amplification with high saturation power. Due to the high critical magnetic fields of high-kinetic-inductance materials, KI-TWPAs should be resilient to magnetic fields. In this work, we study how magnetic field and temperature affect the performance of a KI-TWPA based on a thin-NbTiN inverse microstrip with a Nb ground plane. This KI-TWPA can provide substantial signal-to-noise ratio improve…

The US FTC sues Key Investment Group, operator of sites like TotalTickets.com, for skirting ticket limits to buy up and resell live event tickets at a markup (Jody Godoy/Reuters)
https://www.reuters.com/sustainability/boa…

Even among the conservatives who have voiced concerns, there are limits to how self-critical they appear willing to be
Many see little use in pointing the finger now at anyone but liberals.
And few of them have defended Mr. Kimmel, who has made President Trump and his followers the butt of his jokes for years.

I derailed myself again, so I decided to set limits on it…
Creating Through Limitations - Scales of Creation
#creativity #MusicTheory

Creating Through Limitations - Scales of Creation
Stan Stewart - @muz4now

Trump Admin Limits Mexican Flights, Threatens Delta Alliance | Associated Press
https://www.newsmax.com/newsfront/trump-administration-mexico-delta/2025/07/19/id/1219324/

Pushing the Limits of End-to-End Diarization
Samuel J. Broughton, Lahiru Samarakoon
https://arxiv.org/abs/2509.14737 https://arxiv.org/pdf/2509.14737

Pushing the Limits of End-to-End Diarization
In this paper, we present state-of-the-art diarization error rates (DERs) on multiple publicly available datasets, including AliMeeting-far, AliMeeting-near, AMI-Mix, AMI-SDM, DIHARD III, and MagicData RAMC. Leveraging EEND-TA, a single unified non-autoregressive model for end-to-end speaker diarization, we achieve new benchmark results, most notably a DER of 14.49% on DIHARD III. Our approach scales pretraining through 8-speaker simulation mixtures, ensuring each generated speaker mixture conf…

Integrated Sensing and Communication for Vehicular Networks: A Rate-Distortion Fundamental Limits of State Estimator
Lugaoze Feng, Guocheng Lv, Xunan Li, Ye Jin
https://arxiv.org/abs/2509.15025

Integrated Sensing and Communication for Vehicular Networks: A Rate-Distortion Fundamental Limits of State Estimator
The state-dependent memoryless channel (SDMC) is employed to model the integrated sensing and communication (ISAC) system for connected vehicular networks, where the transmitter conveys messages to the receiver while simultaneously estimating the state parameter of interest via the received echo signals. However, the performance of sensing has often been neglected in existing works. To address this gap, we establish the rate-distortion function for sensing performance in the SDMC model, which i…

Probing the limits of cosmological information from the Lyman-$\alpha$ forest 2-point correlation functions
Wynne Turner, Andrei Cuceu, Paul Martini, J. Aguilar, S. Ahlen, A. Anand, D. Bianchi, D. Brooks, L. Casas, T. Claybaugh, A. de la Macorra, B. Dey, P. Doel, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, E. Gazta\~naga, S. Gontcho A Gontcho, G. Gutierrez, H. K. Herrera-Alcantar, K. Honscheid, M. Ishak, R. Joyce, R. Kehoe, D. Kirkby, A. Kremin, O. Lahav, M. Landriau, L. Le Guillo…

Probing the limits of cosmological information from the Lyman-$α$ forest 2-point correlation functions
The standard cosmological analysis with the Ly$α$ forest relies on a continuum fitting procedure that suppresses information on large scales and distorts the three-dimensional correlation function on all scales. In this work, we present the first cosmological forecasts without continuum fitting distortion in the Ly$α$ forest, focusing on the recovery of large-scale information. Using idealized synthetic data, we compare the constraining power of the full shape of the Ly$α$ forest auto-correl…

If you've been paying attention, this is a *very* strong signal that OpenAI is hitting the limits of improved capability with more compute/data and they're (predictably) all out of other ideas. The quiet "exponential model capabilities" lie here is what Altmann promised but is now starting not to be able to deliver, even in cherry-picked demo terms.
https://www.cnbc.com/2025/08/11/sam-altman-says-agi-is-a-pointless-term-experts-agree.html
The "agentic" turn was never going to pan out, because it exposes the unreliability of LLMs too directly, and it turns out that no amount of yelling at your text vending machine to "Be smarter! Think harder!" will actually get you anything more than vended text.
I'm *praying* that we get into this crash sooner rather than later, since the faster it comes, the less painful it will be.
My recent reading in actual research papers corroborates this, for example, asking LLMs to play games exposes their utter lack of anything that can be termed "reasoning":
https://arxiv.org/pdf/2508.08501v1

I live by the conviction that anarchism is not a fixed goal to be reached, nor a perfect order to be imposed upon life. Every system that claims finality becomes a prison, and every so‑called final solution turns into domination over human beings. Anarchism, for me, stands in opposition to this tendency, it is the refusal to accept limits set by authority, dogma, or any power that seeks to bind the living stream of human development.
To me, anarchism is not the end of history, but the …

US proposes zero new protections for traded wildlife at upcoming CITES CoP https://news.mongabay.com/2025/08/us-proposes-zero-new-protections-for-traded-wildlife-at-upcoming-cites-cop/

US proposes zero new protections for traded wildlife at upcoming CITES CoP
At the end of 2025, representatives from 185 countries will convene in Uzbekistan to discuss the fate of sharks, African hornbills, hyenas, vultures, palm trees and other threatened species. The group’s decisions will, in part, decide the survival and the future of widely traded fauna and flora as they vote whether to set limits on or […]

Existence, asymptotic behaviors, and high-dimensional uniqueness of topological solutions to the skew-symmetric Chern-Simons system on lattice graphs
Honggang Liu
https://arxiv.org/abs/2509.14538

Existence, asymptotic behaviors, and high-dimensional uniqueness of topological solutions to the skew-symmetric Chern-Simons system on lattice graphs
In this paper, we consider the topological solutions to the skew-symmetric Chern-Simons system on lattice graphs: $$\left\{\begin{aligned} Δu &=λ\mathrm{e}^{\upsilon}(\mathrm{e}^{u}-1)+4π\sum\limits_{j=1}^{k_1}m_jδ_{p_j}, Δ\upsilon&=λ\mathrm{e}^{u}(\mathrm{e}^{\upsilon}-1)+4π\sum\limits_{j=1}^{k_2}n_jδ_{q_j}, \end{aligned} \right. $$ here, $λ\in\mathbb{R}_+$, $k_1$ and $k_2$ are two positive integers, $m_j\in\mathbb{N}\, (j=1,2,\cdot\cdot\cdot,k_1)$, $n_j\in\mathbb{N}\,(j=1,2,\cdot\cdo…

Sources: Anthropic refused federal law enforcement requests to use its AI models for some tasks, such as the surveillance of US citizens, irking the White House (Reed Albergotti/Semafor)
https://www.semafor.com/article/09/17/2025

Anthropic irks White House with limits on models’ use
The AI company declined to allow requests by contractors working with federal law enforcement.

Pushing the Limits of Frequency Analysis in Leakage Abuse Attacks
Nathaniel Moyer, Charalampos Papamanthou, Evgenios Kornaropoulos
https://arxiv.org/abs/2508.11563 https://

Pushing the Limits of Frequency Analysis in Leakage Abuse Attacks
Searchable encryption (SE) is the most scalable cryptographic primitive for searching on encrypted data. Typical SE constructions often allow access-pattern leakage, revealing which encrypted records are retrieved in the server's responses. All the known generic cryptanalyses assume either that the queries are issued uniformly at random or that the attacker observes the search-pattern leakage. It remains unclear what can be reconstructed when using only the access-pattern leakage and knowledge …

Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning
Yeongbin Seo, Dongha Lee, Jaehyung Kim, Jinyoung Yeo
https://arxiv.org/abs/2509.15188

Fast and Fluent Diffusion Language Models via Convolutional Decoding and Rejective Fine-tuning
Autoregressive (AR) language models generate text one token at a time, which limits their inference speed. Diffusion-based language models offer a promising alternative, as they can decode multiple tokens in parallel. However, we identify a key bottleneck in current diffusion LMs: the long decoding-window problem, where tokens generated far from the input context often become irrelevant or repetitive. Previous solutions like semi-autoregressive address this issue by splitting windows into block…

Wisdom of the Crowd: Reinforcement Learning from Coevolutionary Collective Feedback
Wenzhen Yuan, Shengji Tang, Weihao Lin, Jiacheng Ruan, Ganqu Cui, Bo Zhang, Tao Chen, Ting Liu, Yuzhuo Fu, Peng Ye, Lei Bai
https://arxiv.org/abs/2508.12338

Wisdom of the Crowd: Reinforcement Learning from Coevolutionary Collective Feedback
Reinforcement learning (RL) has significantly enhanced the reasoning capabilities of large language models (LLMs), but its reliance on expensive human-labeled data or complex reward models severely limits scalability. While existing self-feedback methods aim to address this problem, they are constrained by the capabilities of a single model, which can lead to overconfidence in incorrect answers, reward hacking, and even training collapse. To this end, we propose Reinforcement Learning from Coev…

Enhancing Targeted Adversarial Attacks on Large Vision-Language Models through Intermediate Projector Guidance
Yiming Cao, Yanjie Li, Kaisheng Liang, Yuni Lai, Bin Xiao
https://arxiv.org/abs/2508.13739

Enhancing Targeted Adversarial Attacks on Large Vision-Language Models through Intermediate Projector Guidance
Targeted adversarial attacks are essential for proactively identifying security flaws in Vision-Language Models before real-world deployment. However, current methods perturb images to maximize global similarity with the target text or reference image at the encoder level, collapsing rich visual semantics into a single global vector. This limits attack granularity, hindering fine-grained manipulations such as modifying a car while preserving its background. Furthermore, these methods largely ov…

Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management
Tianheng Ling, Vipin Singh, Chao Qian, Felix Biessmann, Gregor Schiele
https://arxiv.org/abs/2508.13905

Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management
Extreme weather events, intensified by climate change, increasingly challenge aging combined sewer systems, raising the risk of untreated wastewater overflow. Accurate forecasting of sewer overflow basin filling levels can provide actionable insights for early intervention, helping mitigating uncontrolled discharge. In recent years, AI-based forecasting methods have offered scalable alternatives to traditional physics-based models, but their reliance on cloud computing limits their reliability …

#WritersCoffeeClub
16. What was the hardest writerly lesson for you to learn? Or unlearn?
17. Should modern writers worry about proving their work is not generated by an LLM?
18. Have you written something blasphemous? Tell us about it.
---
16. How to cut words and squeeze myself into character limits.
That's why I generally do not set character limits.

Neural Earthquake Forecasting with Minimal Information: Limits, Interpretability, and the Role of Markov Structure
Jonas Koehler, Nishtha Srivastava, Kai Zhou, Claudia Quinteros, Johannes Faber, F. Alejandro Nava
https://arxiv.org/abs/2509.14661

Neural Earthquake Forecasting with Minimal Information: Limits, Interpretability, and the Role of Markov Structure
Forecasting earthquake sequences remains a central challenge in seismology, particularly under non-stationary conditions. While deep learning models have shown promise, their ability to generalize across time remains poorly understood. We evaluate neural and hybrid (NN plus Markov) models for short-term earthquake forecasting on a regional catalog using temporally stratified cross-validation. Models are trained on earlier portions of the catalog and evaluated on future unseen events, enabling r…

“This is not a hoax, and it’s not going away,”
said Epstein survivor Marina Lacerda.
Trump’s struggles reveal the limits of his usual tactics.
His strategy
—harnessing the anger caused by inequality to deflect blame
—has faltered here.
To understand why, we must look beyond Epstein as a predator to examine the system that protected him.
Documents recently released from Epstein’s estate expose the extent of his aristocratic immunity.
In a 2008 plea …

The real reason Donald Trump can’t escape the Epstein scandal
Donald Trump’s usual tactics to deflect blame are failing as victims of Jeffrey Epstein expose the deep inequalities that protected the predator, and now implicate Trump himself.

BOW: Bayesian Optimization over Windows for Motion Planning in Complex Environments
Sourav Raxit, Abdullah Al Redwan Newaz, Paulo Padrao, Jose Fuentes, Leonardo Bobadilla
https://arxiv.org/abs/2508.13052

BOW: Bayesian Optimization over Windows for Motion Planning in Complex Environments
This paper introduces the BOW Planner, a scalable motion planning algorithm designed to navigate robots through complex environments using constrained Bayesian optimization (CBO). Unlike traditional methods, which often struggle with kinodynamic constraints such as velocity and acceleration limits, the BOW Planner excels by concentrating on a planning window of reachable velocities and employing CBO to sample control inputs efficiently. This approach enables the planner to manage high-dimension…

Evaluating the Effectiveness of Coverage-Guided Fuzzing for Testing Deep Learning Library APIs
Feiran Qin, M. M. Abid Naziri, Hengyu Ai, Saikat Dutta, Marcelo d'Amorim
https://arxiv.org/abs/2509.14626

Evaluating the Effectiveness of Coverage-Guided Fuzzing for Testing Deep Learning Library APIs
Deep Learning (DL) libraries such as PyTorch provide the core components to build major AI-enabled applications. Finding bugs in these libraries is important and challenging. Prior approaches have tackled this by performing either API-level fuzzing or model-level fuzzing, but they do not use coverage guidance, which limits their effectiveness and efficiency. This raises an intriguing question: can coverage guided fuzzing (CGF), in particular frameworks like LibFuzzer, be effectively applied to …

New student loan limits pose threat to nursing
https://thehill.com/opinion/healthcare/5408600-student-loan-caps-threaten-healthcare/

Gauge origami and quiver W-algebras IV: Pandharipande--Thomas $qq$-characters
Taro Kimura, Go Noshita
https://arxiv.org/abs/2508.12125 https://arxiv.org/pd…

Gauge origami and quiver W-algebras IV: Pandharipande--Thomas $qq$-characters
We develop a contour integral formalism for computing the K-theoretic equivariant 3-vertex. Within the Jeffrey--Kirwan (JK) residue framework, we show that, by an appropriate choice of the reference vector, both the equivariant Donaldson--Thomas (DT) and Pandharipande--Thomas (PT) 3-vertices can be extracted from the same integrand. We analyze three distinct limits of the PT 3-vertex, recovering the unrefined topological vertex, the refined topological vertex, and the Macdonald refined topologi…

"‘Alarmingly high’ levels of forever chemicals found at airports in England, investigation reveals"
#UK #UnitedKingdom #PFAS

Stochasticity in Stellar Yields Reflected in Theoretical Dust Masses Estimates Across all Type II Supernova Progenitors
Archana Purushothaman, Arkaprabha Sarangi, S. K. Jeena
https://arxiv.org/abs/2508.12933

Stochasticity in Stellar Yields Reflected in Theoretical Dust Masses Estimates Across all Type II Supernova Progenitors
Core-collapse supernovae (CCSNe) are among the primary sources of dust in galaxies. In this study, we derive theoretical upper limits on dust masses as a function of supernova (SN) progenitors with initial masses between 9 and 120 Msun, based on previously established models of dust formation chemistry in CCSNe. We find that O-rich dust, particularly silicates, dominates the dust budget, with masses ranging from 0.02 to 0.9 Msun, and that the total mass of O-rich dust increases with progenitor …

D4PM: A Dual-branch Driven Denoising Diffusion Probabilistic Model with Joint Posterior Diffusion Sampling for EEG Artifacts Removal
Feixue Shao, Xueyu Liu, Yongfei Wu, Jianbo Lu, Guiying Yan, Weihua Yang
https://arxiv.org/abs/2509.14302

D4PM: A Dual-branch Driven Denoising Diffusion Probabilistic Model with Joint Posterior Diffusion Sampling for EEG Artifacts Removal
Artifact removal is critical for accurate analysis and interpretation of Electroencephalogram (EEG) signals. Traditional methods perform poorly with strong artifact-EEG correlations or single-channel data. Recent advances in diffusion-based generative models have demonstrated strong potential for EEG denoising, notably improving fine-grained noise suppression and reducing over-smoothing. However, existing methods face two main limitations: lack of temporal modeling limits interpretability and t…

ARDENT: A Python package for fast dynamical detection limits with radial velocities
Manu Stalport, Micha\"el Cretignier, Luca Naponiello, Val\'erie Van Grootel
https://arxiv.org/abs/2509.13521

ARDENT: A Python package for fast dynamical detection limits with radial velocities
The architecture of planetary systems is a key piece of information to our understanding of their formation and evolution. This information also allows us to place the Solar System in the exoplanet context. An important example is the impact of outer giant planets on the formation of inner super-Earths and sub-Neptunes. Radial velocity (RV) surveys aim at drawing statistical insights into the (anti-)correlations between giants and inner small planets, which remain unclear. These surveys are lim…

Thermal Conductivity Limits of MoS$_2$ and MoSe$_2$: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
Tugbey Kocabas, Murat Keceli, Tanju Gurel, Milorad Milosevic, Cem Sevik
https://arxiv.org/abs/2509.13798

Thermal Conductivity Limits of MoS$_2$ and MoSe$_2$: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
Group-VI transition metal dichalcogenides (TMDs), MoS$_2$ and MoSe$_2$, have emerged as prototypical low-dimensional systems with distinctive phononic and electronic properties, making them attractive for applications in nanoelectronics, optoelectronics, and thermoelectrics. Yet, their reported lattice thermal conductivities ($κ$) remain highly inconsistent, with experimental values and theoretical predictions differing by more than an order of magnitude. These discrepancies stem from uncertai…

Entropy-patch choked-nozzle interaction: quasi-steady and inertial modeling regimes mapped and limits of linearization established
Karim Elbakly, Steven John Hulshoff, Friedrich Bake, Cornelis Venner, Lionel Hirschberg
https://arxiv.org/abs/2509.14007

Entropy-patch choked-nozzle interaction: quasi-steady and inertial modeling regimes mapped and limits of linearization established
The effects of entropy-patch shape, size, and strength on the upstream acoustic response generated by entropy-patch choked-nozzle interactions are investigated. Numerical-simulation-based investigations, using a two-dimensional planar Euler code, reveal the existence of two distinct modeling regimes: the quasi-steady (matching-condition) regime and the inertial regime, respectively. The ratio of the entropy-patch streamwise length scale to the nozzle throat height was found to be an order param…

📸 Automated speed enforcement significantly reduces speeding in Toronto school zones
https://medicalxpress.com/news/2025-07-automated-significantly-toronto-school-zones.html

Automated speed enforcement significantly reduces speeding in Toronto school zones
Despite lower speed limits in school zones, child pedestrian injuries are most common near schools. Now, a new study led by researchers at The Hospital for Sick Children (SickKids) and Toronto Metropolitan University (TMU) has found that automated speed enforcement (ASE) cameras reduced the number of speeding vehicles by 45 percent in urban school zones.

PFD or PDF: Rethinking the Probability of Failure in Mitigation Safety Functions
Hamid Jahanian
https://arxiv.org/abs/2508.12814 https://arxiv.org/pdf/2508…

PFD or PDF: Rethinking the Probability of Failure in Mitigation Safety Functions
SIL (Safety Integrity Level) allocation plays a crucial role in defining the design requirements for Safety Functions (SFs) within high-risk industries. SIL is typically determined based on the estimated Probability of Failure on Demand (PFD), which must remain within permissible limits to manage risk effectively. Extensive research has been conducted on determining target PFD and SIL, with a stronger emphasis on preventive SFs than on mitigation SFs. In this paper, we address a rather conceptu…

Searching for continuous gravitational waves in the Parkes Pulsar Timing Array DR3
Shi-Yi Zhao, Zu-Cheng Chen, Jacob Cardinal Tremblay, Boris Goncharov, Xing-Jiang Zhu, N. D. Ramesh Bhat, Ma{\l}gorzata Cury{\l}o, Shi Dai, Valentina Di Marco, Hao Ding, George Hobbs, Agastya Kapur, Wenhua Ling, Tao Liu, Rami Mandow, Saurav Mishra, Daniel J. Reardon, Christopher J Russell, Ryan M. Shannon, Shuangqiang Wang, Lei Zhang, Andrew Zic

Searching for continuous gravitational waves in the Parkes Pulsar Timing Array DR3
We present results from an all-sky search for continuous gravitational waves from individual supermassive binary black holes using the third data release (DR3) of the Parkes Pulsar Timing Array (PPTA). Even though we recover a common-spectrum stochastic process, potentially induced by a nanohertz gravitational wave background, we find no evidence of continuous waves. Therefore, we place upper limits on the gravitational-wave strain amplitude: in the most sensitive frequency range around 10 nHz,…

"If you always put limits on everything you do, physical or anything else. It will spread into your work and into your life. There are no limits. There are only plateaus, and you must not stay there, you must go beyond them."
-Bruce Lee
#acting #coaching

Fiber bundle model of thermally activated creep failure
Stefan Hiemer, Paolo Moretti, Stefano Zapperi, Michael Zaiser
https://arxiv.org/abs/2508.13367 https://

Fiber bundle model of thermally activated creep failure
An equal load sharing fiber bundle model for thermally activated breakdown is developed using transition state theory to describe the rate of elementary failures. The lifetime distribution, average, variance and their asymptotic limits for uniform fiber failure thresholds are derived and found to be in excellent agreement with simulations. The asymptotic scaling with regards to the number of fibers matches analytical approximations in the low temperature limit derived by Roux and co-workers for…

heise | Googles Video-KI Veo 3 ausprobiert: Kosten, Funktionen, Limits
Veo 3 verspricht fotorealistische KI-Videos mit Sound, jetzt auch in Deutschland. Das müssen Sie wissen, bevor Sie für den Google-Dienst bezahlen.

On the closure of a plane ray that limits onto itself
David S. Lipham
https://arxiv.org/abs/2509.13598 https://arxiv.org/pdf/2509.13598

On the closure of a plane ray that limits onto itself
We show that the closure of any self-entwined ray in the plane must contain an uncountable collection of pairwise-disjoint subcontinua. This is false in dimension three.

"A commitment to continue to be appalled by the situation in Gaza. But not to be so appalled that either country would actually do anything about it."
https://www.theguardian.com/politics/2025/

Data-driven optimized high-order WENO schemes with low-dissipation and low-dispersion
Jinrui Zhou, Yiqi Gu, Song Jiang, Hua Shen, Liwei Xu, Guanyu Zhou
https://arxiv.org/abs/2508.13190

Data-driven optimized high-order WENO schemes with low-dissipation and low-dispersion
Classical high-order weighted essentially non-oscillatory (WENO) schemes are designed to achieve optimal convergence order for smooth solutions and to maintain non-oscillatory behaviors for discontinuities. However, their spectral properties are not optimal, which limits the ability to capture high-frequency waves and small-scale features. In this paper, we propose a data-driven optimized method to improve the spectral properties of the WENO schemes. By analyzing the approximate dispersion rela…

Toxic Pfas above proposed safety limits in almost all English waters tested https://www.theguardian.com/environment/2025/jul/11/toxic-pfas-above-proposed-safety-limits-in-almost-all-english-waters-tested

Multi-Plasticity Synergy with Adaptive Mechanism Assignment for Training Spiking Neural Networks
Yuzhe Liu, Xin Deng, Qiang Yu
https://arxiv.org/abs/2508.13673 https://

Multi-Plasticity Synergy with Adaptive Mechanism Assignment for Training Spiking Neural Networks
Spiking Neural Networks (SNNs) are promising brain-inspired models known for low power consumption and superior potential for temporal processing, but identifying suitable learning mechanisms remains a challenge. Despite the presence of multiple coexisting learning strategies in the brain, current SNN training methods typically rely on a single form of synaptic plasticity, which limits their adaptability and representational capability. In this paper, we propose a biologically inspired training…

Projective limits in Euclidean quantum field theory, I: Free scalar fields
Svetoslav Zahariev
https://arxiv.org/abs/2509.12498 https://arxiv.org/pdf/2509.1…

Projective limits in Euclidean quantum field theory, I: Free scalar fields
We present two constructions of projective systems of measures associated to discretizations of free scalar Euclidean quantum fields. The first one is obtained using only purely combinatorial data and applies to free massless scalar fields on polyhedral cell complexes. The second construction utilizes the suitably discretized covariance of the free massive scalar field on a compact Riemannian manifold.

The Design and Performance Characteristics of the NRL4 ASIC Developed for the COSI Small Explorer Gamma-ray Satellite
Jarred M. Roberts, Clio Sleator, Eric Wulf, Steven E. Boggs, Gianluigi De Geronimo, Alex Lowell, Brent Mochizuki, John A. Tomsick
https://arxiv.org/abs/2508.11839

The Design and Performance Characteristics of the NRL4 ASIC Developed for the COSI Small Explorer Gamma-ray Satellite
Next-generation gamma-ray observatories aim to enable precision measurements in high-energy astrophysics using advanced semiconductor detector technologies. Meeting the scientific requirements of modern instruments demands detector systems that provide high spatial and spectral resolution across large detection areas, with strict limits on power consumption and mass. These needs drive innovation in front-end electronics and mixed-signal processing to support compact detector electrode geometrie…

TSA may ease liquid size limits next, Noem says (Kelly Tyko/Axios)
https://www.axios.com/2025/07/16/tsa-liquid-carry-on-restrictions-airplane-security
http://www.memeorandum.com/250716/p171#a250716p171

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
Elijah Pelofske, Marek Rams, Andreas B\"artschi, Piotr Czarnik, Paolo Braccia, Lukasz Cincio, Stephan Eidenbenz
https://arxiv.org/abs/2509.13528

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One of the primary limitations of QAOA is the task of finding a set of good parameters. Parameter transfer is a phenomenon where QAOA angles trained on problem instances that are self-similar tend to perform well for other problem instances from that similar class. This suggests a potentially highly efficient and scalable…

David Ellison's lack of news expertise, combined with his changes at Paramount Skydance, indicate tough times ahead for CBS News and its staff (Richard J. Tofel/Second Rough Draft)
https://dicktofel.substack.com/p/cbs-news-and-the-first-moves-of-its

CBS News and the First Moves of its Nepo Baby Owner
Learning about the limits of billionaires

Chabauty limits of fixed point groups of $p$-adic involutions
Corina Ciobotaru
https://arxiv.org/abs/2509.11202 https://arxiv.org/pdf/2509.11202

Chabauty limits of fixed point groups of $p$-adic involutions
We study Chabauty limits of the fixed-point group of $k$-points $H_k$ associated with an involutive $k$-automorphism $θ$ of a connected linear reductive group $G$ defined over a non-Archimedean local field $k$ of characteristic zero. Leveraging the geometry of the Bruhat--Tits building, the structure of $(θ,k)$-split tori, and the $K\mathcal{B}_kH_k$ decomposition of $G_k$, we establish that any nontrivial Chabauty limit $L$ of $H_k$ is $G_k$-conjugate to a subgroup of $$U_{σ_+}(k) \rtimes (…

The Trump administration on Thursday said it will restrict waivers that have allowed states to keep kids enrolled in Medicaid or the Children’s Health Insurance Program beyond the 12-month period of continuous coverage required under federal law.
The Centers for Medicare and Medicaid Services (CMS), led by Mehmet Oz, announced the move on Thursday, saying that it has informed states of a “clear shift away from policies that extend beyond statutory limits,”
specifically restricting…

'Terrible Development': Trump Admin Restricts State Efforts to Help Kids Stay on Medicaid | Common Dreams
"The Trump administration will stop at nothing to rip coverage away from American families, even kids they claim they want to protect," said Sen. Ron Wyden.

Detecting Pipeline Failures through Fine-Grained Analysis of Web Agents
Daniel R\"oder, Akhil Juneja, Roland Roller, Sven Schmeier
https://arxiv.org/abs/2509.14382 https://…

Detecting Pipeline Failures through Fine-Grained Analysis of Web Agents
Web agents powered by large language models (LLMs) can autonomously perform complex, multistep tasks in dynamic web environments. However, current evaluations mostly focus on the overall success while overlooking intermediate errors. This limits insight into failure modes and hinders systematic improvement. This work analyzes existing benchmarks and highlights the lack of fine-grained diagnostic tools. To address this gap, we propose a modular evaluation framework that decomposes agent pipeline…

Refining the deep sub-barrier 12C 12C excitation function with STELLA
J. Nippert, S. Courtin, M. Heine, D. G. Jenkins, P. Adsley, A. Bonhomme, R. Canavan, D. Curien, T. Dumont, E. Gregor, G. Harmant, E. Monpribat, L. Morrison, M. Moukaddam, M. Richer, M. Rudigier, J. G. Vega Romero, W. N. Catford, P. Cotte, S. Della Negra, G. Haefner, F. Hammache, J. Lesrel, S. Pascu, Zs. Podoly\'ak, P. H. Regan, I. Ribaud, N. de S\'er\'eville, C. Stodel, J. Vesi\'c

Refining the deep sub-barrier 12C+12C excitation function with STELLA
Purpose: We have investigated the cross section around the lowest direct coincident gamma-particle measurements, where previously only limits could be established with the aim of obtaining a detailed description of the excitation function. We have furthermore analysed the ratio of extreme decay branching into the first excited state of daughter nuclei with alpha or proton emission at relative kinetic energies where previous measurements are in disagreement with each other. Conclusions: Our find…

Large Language Model probabilities cannot distinguish between possible and impossible language
Evelina Leivada, Raquel Montero, Paolo Morosi, Natalia Moskvina, Tamara Serrano, Marcel Aguilar, Fritz Guenther
https://arxiv.org/abs/2509.15114

Large Language Model probabilities cannot distinguish between possible and impossible language
A controversial test for Large Language Models concerns the ability to discern possible from impossible language. While some evidence attests to the models' sensitivity to what crosses the limits of grammatically impossible language, this evidence has been contested on the grounds of the soundness of the testing material. We use model-internal representations to tap directly into the way Large Language Models represent the 'grammatical-ungrammatical' distinction. In a novel benchmark, we elicit…

Sources: OpenAI plans to spend ~$100B on backup servers from cloud providers through 2030, in addition to the $350B already projected for server rentals (Sri Muppidi/The Information)
https://www.theinformation.com/articles/openai-spend-100-bil…

OpenAI to Spend $100 Billion on Backup Servers for AI Breakthroughs
When OpenAI in March released ChatGPT features that could turn photos into animated characters, a spike in usage forced the company to put temporary limits on the features. It wasn’t the first time this had happened. Chief Financial Officer Sarah Friar told investors at a Goldman Sachs ...

Re-weighting estimator for ab initio path integral Monte Carlo simulations of fictitious identical particles
Tobias Dornheim, Pontus Svensson, Paul Hamann, Sebastian Schwalbe, Zhandos Moldabekov, Panagiotis Tolias, Jan Vorberger
https://arxiv.org/abs/2508.12323

Re-weighting estimator for ab initio path integral Monte Carlo simulations of fictitious identical particles
The fermion sign problem constitutes one of the most fundamental obstacles in quantum many-body theory. Recently, it has been suggested to circumvent the sign problem by carrying out path integral simulations with a fictitious quantum statistics variable $ξ$, which allows for a smooth interpolation between the bosonic and fermionic limits [\textit{J.~Chem.~Phys.}~\textbf{157}, 094112 (2022)]. This $ξ$-extrapolation method has subsequently been applied to a variety of systems and has facilitat…

A Category Theory Framework for Macroeconomic Modeling: The Case of Argentina's Bimonetary Economy
Luciano Pollicino
https://arxiv.org/abs/2508.13233 https://

A Category Theory Framework for Macroeconomic Modeling: The Case of Argentina's Bimonetary Economy
Traditional macroeconomic models, based on static algebraic systems, fail to capture the dynamics of a bimonetary economy like Argentina's. This paper proposes a framework based on category theory to develop a more flexible and structured model that represents the evolving relationships between key variables such as inflation expectations, interest rates, and currency demand. Using concepts like objects, morphisms, learning/forgetful functors, limits, and colimits, the model is applied to empir…

Energy-Constrained Navigation for Planetary Rovers under Hybrid RTG-Solar Power
Tianxin Hu, Weixiang Guo, Ruimeng Liu, Xinhang Xu, Rui Qian, Jinyu Chen, Shenghai Yuan, Lihua Xie
https://arxiv.org/abs/2509.15062

Energy-Constrained Navigation for Planetary Rovers under Hybrid RTG-Solar Power
Future planetary exploration rovers must operate for extended durations on hybrid power inputs that combine steady radioisotope thermoelectric generator (RTG) output with variable solar photovoltaic (PV) availability. While energy-aware planning has been studied for aerial and underwater robots under battery limits, few works for ground rovers explicitly model power flow or enforce instantaneous power constraints. Classical terrain-aware planners emphasize slope or traversability, and trajector…

MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies
Weiwei Qi, Shuo Shao, Wei Gu, Tianhang Zheng, Puning Zhao, Zhan Qin, Kui Ren
https://arxiv.org/abs/2508.13048

MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies
Large Language Models (LLMs) have exhibited remarkable capabilities but remain vulnerable to jailbreaking attacks, which can elicit harmful content from the models by manipulating the input prompts. Existing black-box jailbreaking techniques primarily rely on static prompts crafted with a single, non-adaptive strategy, or employ rigid combinations of several underperforming attack methods, which limits their adaptability and generalization. To address these limitations, we propose MAJIC, a Mark…

SAQ: Pushing the Limits of Vector Quantization through Code Adjustment and Dimension Segmentation
Hui Li, Shiyuan Deng, Xiao Yan, Xiangyu Zhi, James Cheng
https://arxiv.org/abs/2509.12086

SAQ: Pushing the Limits of Vector Quantization through Code Adjustment and Dimension Segmentation
Approximate Nearest Neighbor Search (ANNS) plays a critical role in applications such as search engines, recommender systems, and RAG for LLMs. Vector quantization (VQ), a crucial technique for ANNS, is commonly used to reduce space overhead and accelerate distance computations. However, despite significant research advances, state-of-the-art VQ methods still face challenges in balancing encoding efficiency and quantization accuracy. To address these limitations, we propose a novel VQ method ca…

Joint Scheduling and Multiflow Maximization in Wireless Networks
Yanxiao Liu, Shenghao Yang, Cheuk Ting Li
https://arxiv.org/abs/2509.14582 https://arxiv.o…

Joint Scheduling and Multiflow Maximization in Wireless Networks
Towards the development of 6G mobile networks, it is promising to integrate a large number of devices from multi-dimensional platforms, and it is crucial to have a solid understanding of the theoretical limits of large-scale networks. We revisit a fundamental problem at the heart of network communication theory: the maximum multiflow (MMF) problem in multi-hop networks, with network coding performed at intermediate nodes. To derive the exact-optimal solution to the MMF problem (as opposed to ap…

Cross-diffusion limits in multispecies kinetic models
Ansgar J\"ungel, Annamaria Pollino, Satoshi Taguchi
https://arxiv.org/abs/2509.14046 https://arx…

Cross-diffusion limits in multispecies kinetic models
Cross-diffusion systems are formally derived from multispecies kinetic models in the diffusion limit. The first limit in the multispecies BGK model of Gross and Krook leads to a variant of the non-isothermal Maxwell-Stefan equations. The second limit in a BGK model with Brinkman-type force term yields generalized Busenberg-Travis equations, which reduce for constant temperature to the classical Busenberg-Travis system for segregating population species. Entropy equalities are derived for the ki…

Deploying UDM Series in Real-Life Stuttered Speech Applications: A Clinical Evaluation Framework
Eric Zhang (SSHealth Team, AI for Healthcare Laboratory), Li Wei (SSHealth Team, AI for Healthcare Laboratory), Sarah Chen (SSHealth Team, AI for Healthcare Laboratory), Michael Wang (SSHealth Team, AI for Healthcare Laboratory)
https://arxiv.o…

Deploying UDM Series in Real-Life Stuttered Speech Applications: A Clinical Evaluation Framework
Stuttered and dysfluent speech detection systems have traditionally suffered from the trade-off between accuracy and clinical interpretability. While end-to-end deep learning models achieve high performance, their black-box nature limits clinical adoption. This paper looks at the Unconstrained Dysfluency Modeling (UDM) series-the current state-of-the-art framework developed by Berkeley that combines modular architecture, explicit phoneme alignment, and interpretable outputs for real-world clini…

Geometric optimization for quantum communication
Chengkai Zhu, Hongyu Mao, Kun Fang, Xin Wang
https://arxiv.org/abs/2509.15106 https://arxiv.org/pdf/2509.1…

Geometric optimization for quantum communication
Determining the ultimate limits of quantum communication, such as the quantum capacity of a channel and the distillable entanglement of a shared state, remains a central challenge in quantum information theory, primarily due to the phenomenon of superadditivity. This work develops Riemannian optimization methods to establish significantly tighter, computable two-sided bounds on these fundamental quantities. For upper bounds, our method systematically searches for state and channel extensions th…

Towards Open-Ended Emotional Support Conversations in LLMs via Reinforcement Learning with Future-Oriented Rewards
Ting Yang, Li Chen, Huimin Wang
https://arxiv.org/abs/2508.12935

Towards Open-Ended Emotional Support Conversations in LLMs via Reinforcement Learning with Future-Oriented Rewards
Emotional Support Conversation (ESC) systems aim to alleviate users' emotional difficulties and provide long-term, systematic support for emotional well-being. However, most large language model (LLM)-based ESC systems rely on predefined strategies, which limits their effectiveness in complex, real-life scenarios. To enable flexible responses to diverse emotional problem scenarios, this paper introduces a novel end-to-end framework (RLFF-ESC) that directly learns enduring emotionally supportive…

"If you always put limits on everything you do, physical or anything else. It will spread into your work and into your life. There are no limits. There are only plateaus, and you must not stay there, you must go beyond them."
-Bruce Lee
#acting #coaching

Exploiting Convexity of Neural Networks in Dynamic Operating Envelope Optimization for Distributed Energy Resources
Hongyi Li, Liming Liu, Yunyi Li, Zhaoyu Wang
https://arxiv.org/abs/2508.13090

Exploiting Convexity of Neural Networks in Dynamic Operating Envelope Optimization for Distributed Energy Resources
The increasing penetration of distributed energy resources (DERs) brings opportunities and challenges to the operation of distribution systems. To ensure network integrity, dynamic operating envelopes (DOEs) are issued by utilities to DERs as their time-varying export/import power limits. Due to the non-convex nature of power flow equations, the optimization of DOEs faces a dilemma of solution accuracy and computation efficiency. To bridge this gap, in this paper, we facilitate DOE optimization…

LinguaSafe: A Comprehensive Multilingual Safety Benchmark for Large Language Models
Zhiyuan Ning, Tianle Gu, Jiaxin Song, Shixin Hong, Lingyu Li, Huacan Liu, Jie Li, Yixu Wang, Meng Lingyu, Yan Teng, Yingchun Wang
https://arxiv.org/abs/2508.12733

LinguaSafe: A Comprehensive Multilingual Safety Benchmark for Large Language Models
The widespread adoption and increasing prominence of large language models (LLMs) in global technologies necessitate a rigorous focus on ensuring their safety across a diverse range of linguistic and cultural contexts. The lack of a comprehensive evaluation and diverse data in existing multilingual safety evaluations for LLMs limits their effectiveness, hindering the development of robust multilingual safety alignment. To address this critical gap, we introduce LinguaSafe, a comprehensive multi…

RoboRetriever: Single-Camera Robot Object Retrieval via Active and Interactive Perception with Dynamic Scene Graph
Hecheng Wang, Jiankun Ren, Jia Yu, Lizhe Qi, Yunquan Sun
https://arxiv.org/abs/2508.12916

RoboRetriever: Single-Camera Robot Object Retrieval via Active and Interactive Perception with Dynamic Scene Graph
Humans effortlessly retrieve objects in cluttered, partially observable environments by combining visual reasoning, active viewpoint adjustment, and physical interaction-with only a single pair of eyes. In contrast, most existing robotic systems rely on carefully positioned fixed or multi-camera setups with complete scene visibility, which limits adaptability and incurs high hardware costs. We present \textbf{RoboRetriever}, a novel framework for real-world object retrieval that operates using …

To CLEAN or not to CLEAN: Data Processing in the ngVLA era
Hendrik M\"uller
https://arxiv.org/abs/2509.15176 https://arxiv.org/pdf/2509.15176

To CLEAN or not to CLEAN: Data Processing in the ngVLA era
Radio interferometric imaging has long relied on the CLEAN algorithm, valued for its speed, robustness, and integration with calibration pipelines. However, next-generation facilities such as the ngVLA, SKA, and ALMAs Wideband Sensitivity Upgrade will produce data volumes and dynamic ranges that exceed the scalability of traditional methods. CLEAN remains dominant due to its simplicity and accumulated expertise, yet its assumption of modeling the sky as point sources limits its ability to recov…

Hierarchical Graph Feature Enhancement with Adaptive Frequency Modulation for Visual Recognition
Feiyue Zhao, Zhichao Zhang
https://arxiv.org/abs/2508.11497 https://

Hierarchical Graph Feature Enhancement with Adaptive Frequency Modulation for Visual Recognition
Convolutional neural networks (CNNs) have demonstrated strong performance in visual recognition tasks, but their inherent reliance on regular grid structures limits their capacity to model complex topological relationships and non-local semantics within images. To address this limita tion, we propose the hierarchical graph feature enhancement (HGFE), a novel framework that integrates graph-based rea soning into CNNs to enhance both structural awareness and feature representation. HG…

Some US states pass or explore laws aimed at reining in the cost of e-books for libraries, which often pay 10x more for e-book licenses than print copies (Erik Ofgang/New York Times)
https://www.nytimes.com/2025/07/16/books/l…

Some States Are Pushing Back on Library E-Book Licensing Fees
Proposed legislation would pressure publishers to adjust borrowing limits and find other ways to widen access.

Scaling Multi-Agent Epistemic Planning through GNN-Derived Heuristics
Giovanni Briglia, Francesco Fabiano, Stefano Mariani
https://arxiv.org/abs/2508.12840 https://

Scaling Multi-Agent Epistemic Planning through GNN-Derived Heuristics
Multi-agent Epistemic Planning (MEP) is an autonomous planning framework for reasoning about both the physical world and the beliefs of agents, with applications in domains where information flow and awareness among agents are critical. The richness of MEP requires states to be represented as Kripke structures, i.e., directed labeled graphs. This representation limits the applicability of existing heuristics, hindering the scalability of epistemic solvers, which must explore an exponential sear…

LLM-OREF: An Open Relation Extraction Framework Based on Large Language Models
Hongyao Tu, Liang Zhang, Yujie Lin, Xin Lin, Haibo Zhang, Long Zhang, Jinsong Su
https://arxiv.org/abs/2509.15089

LLM-OREF: An Open Relation Extraction Framework Based on Large Language Models
The goal of open relation extraction (OpenRE) is to develop an RE model that can generalize to new relations not encountered during training. Existing studies primarily formulate OpenRE as a clustering task. They first cluster all test instances based on the similarity between the instances, and then manually assign a new relation to each cluster. However, their reliance on human annotation limits their practicality. In this paper, we propose an OpenRE framework based on large language models (…

Quantum Metrology of Spin Sensing with Free Space Electrons
Santiago Beltr\'an-Romero, Michael Gaida, Philipp Haslinger, Dennis R\"atzel, Stefan Nimmrichter
https://arxiv.org/abs/2509.14982

Quantum Metrology of Spin Sensing with Free Space Electrons
Recent advances in transmission electron microscopy (TEM) have opened the path toward spin resonance spectroscopy with single-spin sensitivity. To assess this potential, we investigate the quantum precision limits for sensing magnetic moments with free-electron probes. Using a scattering model where an electron wavepacket interacts with a localized spin, we study two metrological tasks: estimating the magnitude of the magnetic moment and discriminating the presence of a spin. The sensitivity fo…

‘Alarmingly high’ levels of forever chemicals found at airports in England, investigation reveals https://www.theguardian.com/environment/2025/aug/14/alarmingly-high-levels-of-forever-chemicals-found…

Trump's massive tax and spending bill just slapped a cap on how much 𝘸𝘦 can borrow to go to grad school.
Starting July 1, new federal rules limit how much parents and grad students can take out in student loans—𝗻𝗼 𝗺𝗮𝘁𝘁𝗲𝗿 𝘁𝗵𝗲 𝗰𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗱𝗲𝗴𝗿𝗲𝗲.
That means future doctors, teachers, lawyers, and social workers—especially low-income and first-gen students—could be priced out 𝘦𝘯𝘵𝘪𝘳𝘦𝘭𝘺.
The numbers don’t lie:
- $20K annual cap for master’s programs
- $50K per year…

Trump's 'Big Beautiful Bill' imposes new limits to student loan programs, among other changes
The sweeping budget bill cuts grad PLUS loans, institutes lifetime student borrowing caps and imposes new endowment tax policies, but expands Pell Grant eligibility.

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees
Thomas Y. Chen
https://arxiv.org/abs/2509.11054 https://

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees
We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that splits into a modality-balanced term plus a skew penalty $κ\,ΔH$ capturing entropy imbalance and cross-modal redundancy. We then construct an explicit entropy-weighted stochastic quantizer with an adaptive, per-modality temperature decoder; a Blahut-Arimoto …

For the things that make you go hmmm department [1]
[1] see items (4) and (5)

Convergent perturbative series via finite path integral limits: application to energy at strong coupling of the anharmonic oscillator
Ariel Edery
https://arxiv.org/abs/2507.08782 …

Convergent perturbative series via finite path integral limits: application to energy at strong coupling of the anharmonic oscillator
Solving quantum field theories at strong coupling remains a challenging task. The main issue is that the usual perturbative series are asymptotic series which can be useful at weak coupling but break down completely at strong coupling. In this work, we show that if the limits of integration in the path integral are finite, the perturbative series is remarkably an absolutely convergent series which works well at strong coupling. For now, we apply this perturbative approach to $λ\,ϕ^4$ theory i…

"If you always put limits on everything you do, physical or anything else. It will spread into your work and into your life. There are no limits. There are only plateaus, and you must not stay there, you must go beyond them."
—Bruce Lee
#acting #coaching

Quantum Gambling: Best-Arm Strategies for Generator Selection in Adaptive Variational Algorithms
Rick Huang, Artur F. Izmaylov
https://arxiv.org/abs/2509.14917 https://

Quantum Gambling: Best-Arm Strategies for Generator Selection in Adaptive Variational Algorithms
Adaptive variational algorithms suffer from prohibitively high measurement costs during the generator selection step, since energy gradients must be estimated for a large operator pool. This scaling bottleneck limits their applicability to larger molecular systems on near-term quantum devices. We address this challenge by reformulating generator selection as a Best Arm Identification (BAI) problem, where the goal is to identify the generator with the largest energy gradient using as few measure…

Germany-based Q.ANT, which is developing energy-efficient photonic processors for AI and high-performance computing, raised a €62M Series A (Tamara Djurickovic/Tech.eu)
https://tech.eu/2025/07/17/qant-raises-eur62m-to-transform-the…

Q.ANT raises €62M to transform the future of computing with photonic processing
Germany-based Q.ANT, a pioneer in photonic processing, has secured €62 million Series A financing round to accelerate the commercialisation of its energy-efficient photonic processors for artificial intelligence (AI) and high-performance computing (HPC).  As AI infrastructure scales globally, traditional chip technology (CMOS) reaches its physical limits, performance stagnates, and electricity demand is reaching untenable levels. According to a report by the International Energy Agency (IEA…

$S^2M^2$: Scalable Stereo Matching Model for Reliable Depth Estimation
Junhong Min, Youngpil Jeon, Jimin Kim, Minyong Choi
https://arxiv.org/abs/2507.13229

$S^2M^2$: Scalable Stereo Matching Model for Reliable Depth Estimation
The pursuit of a generalizable stereo matching model, capable of performing across varying resolutions and disparity ranges without dataset-specific fine-tuning, has revealed a fundamental trade-off. Iterative local search methods achieve high scores on constrained benchmarks, but their core mechanism inherently limits the global consistency required for true generalization. On the other hand, global matching architectures, while theoretically more robust, have been historically rendered infeas…

Quantum Limited Spatial Resolution of NV-Diamond Magnetometry
Nico Deshler, Declan Daly, Ayan Majumder, Kasturi Saha, Saikat Guha
https://arxiv.org/abs/2508.13438 https://

Quantum Limited Spatial Resolution of NV-Diamond Magnetometry
Optically addressable ensembles of solid-state defects, such as nitrogen vacancy (NV) centers, are a leading modality for imaging-based magnetometry, thermometry and strain sensing. However, monitoring the fluorescence of individual defects within a sub-diffraction ensemble remains an outstanding challenge that currently limits access to atomic-scale features and dynamics. For compact clusters of NVs, imaging-based atomic sensing may be formulated as a low-dimensional multiparameter estimation …

Google updates a Help Center document to clarify Gemini 2.5 Pro usage limits: five prompts per day for free users, 100 prompts for AI Pro, and 500 for AI Ultra (Terrence O'Brien/The Verge)
https://www.theverge.com/news/773496/google-gemini-usage-limits

Google finally details Gemini usage limits
Google finally lets people know how many free Gemini Pro prompts they get a day.

MM-R1: Unleashing the Power of Unified Multimodal Large Language Models for Personalized Image Generation
Qian Liang, Yujia Wu, Kuncheng Li, Jiwei Wei, Shiyuan He, Jinyu Guo, Ning Xie
https://arxiv.org/abs/2508.11433

MM-R1: Unleashing the Power of Unified Multimodal Large Language Models for Personalized Image Generation
Multimodal Large Language Models (MLLMs) with unified architectures excel across a wide range of vision-language tasks, yet aligning them with personalized image generation remains a significant challenge. Existing methods for MLLMs are frequently subject-specific, demanding a data-intensive fine-tuning process for every new subject, which limits their scalability. In this paper, we introduce MM-R1, a framework that integrates a cross-modal Chain-of-Thought (X-CoT) reasoning strategy to unlock …

ZipMPC: Compressed Context-Dependent MPC Cost via Imitation Learning
Rahel Rickenbach, Alan A. Lahoud, Erik Schaffernicht, Melanie N. Zeilinger, Johannes A. Stork
https://arxiv.org/abs/2507.13088

ZipMPC: Compressed Context-Dependent MPC Cost via Imitation Learning
The computational burden of model predictive control (MPC) limits its application on real-time systems, such as robots, and often requires the use of short prediction horizons. This not only affects the control performance, but also increases the difficulty of designing MPC cost functions that reflect the desired long-term objective. This paper proposes ZipMPC, a method that imitates a long-horizon MPC behaviour by learning a compressed and context-dependent cost function for a short-horizon MP…

Real-World Summarization: When Evaluation Reaches Its Limits
Patr\'icia Schmidtov\'a, Ond\v{r}ej Du\v{s}ek, Saad Mahamood
https://arxiv.org/abs/2507.11508

Real-World Summarization: When Evaluation Reaches Its Limits
We examine evaluation of faithfulness to input data in the context of hotel highlights: brief LLM-generated summaries that capture unique features of accommodations. Through human evaluation campaigns involving categorical error assessment and span-level annotation, we compare traditional metrics, trainable methods, and LLM-as-a-judge approaches. Our findings reveal that simpler metrics like word overlap correlate surprisingly well with human judgments (Spearman correlation rank of 0.63), often…

InterKey: Cross-modal Intersection Keypoints for Global Localization on OpenStreetMap
Nguyen Hoang Khoi Tran, Julie Stephany Berrio, Mao Shan, Stewart Worrall
https://arxiv.org/abs/2509.13857

InterKey: Cross-modal Intersection Keypoints for Global Localization on OpenStreetMap
Reliable global localization is critical for autonomous vehicles, especially in environments where GNSS is degraded or unavailable, such as urban canyons and tunnels. Although high-definition (HD) maps provide accurate priors, the cost of data collection, map construction, and maintenance limits scalability. OpenStreetMap (OSM) offers a free and globally available alternative, but its coarse abstraction poses challenges for matching with sensor data. We propose InterKey, a cross-modal framework…

Cross-Granularity Hypergraph Retrieval-Augmented Generation for Multi-hop Question Answering
Changjian Wang, Weihong Deng, Weili Guan, Quan Lu, Ning Jiang
https://arxiv.org/abs/2508.11247

Cross-Granularity Hypergraph Retrieval-Augmented Generation for Multi-hop Question Answering
Multi-hop question answering (MHQA) requires integrating knowledge scattered across multiple passages to derive the correct answer. Traditional retrieval-augmented generation (RAG) methods primarily focus on coarse-grained textual semantic similarity and ignore structural associations among dispersed knowledge, which limits their effectiveness in MHQA tasks. GraphRAG methods address this by leveraging knowledge graphs (KGs) to capture structural associations, but they tend to overly rely on str…

GPT-5's underwhelming performance on benchmarks suggests that the current approach of scaling LLMs is starting to reach the limits of available resources (Financial Times)
https://www.ft.com/content/d01290c9-cc92-4c1f-bd70-ac332cd40f94

Slim-SC: Thought Pruning for Efficient Scaling with Self-Consistency
Colin Hong, Xu Guo, Anand Chaanan Singh, Esha Choukse, Dmitrii Ustiugov
https://arxiv.org/abs/2509.13990 htt…

Slim-SC: Thought Pruning for Efficient Scaling with Self-Consistency
Recently, Test-Time Scaling (TTS) has gained increasing attention for improving LLM reasoning performance at test time without retraining the model. A notable TTS technique is Self-Consistency (SC), which generates multiple reasoning chains in parallel and selects the final answer via majority voting. While effective, the order-of-magnitude computational overhead limits its broad deployment. Prior attempts to accelerate SC mainly rely on model-based confidence scores or heuristics with limited …

Hybrid Fiber-Free-Space Entanglement Distribution Using Off-the-Shelf Quantum Devices
Gustavo C. Amaral, Nienke M. ten Haaf, Breno Perlingeiro, David L. Bakker, Mark G. M. Boekel, Tim E. van Duivenbode, Karthik Selvan, Nicolas Oidtmann, Rafael Ochsendorf, Rick N. M. Wasserman, Mael Flament, Felipe Giraldo, Shane Andrewski, Mehdi Namazi, Federica Facchin, Mario Casta\~neda, Fokko de Vries, Sayali Shevate, Shaurya Bhave, Marco Gorter, Nico Coesel, David Mytling, Mike Mabry, Carlo Page, A…

Hybrid Fiber-Free-Space Entanglement Distribution Using Off-the-Shelf Quantum Devices
Entanglement serves as a fundamental resource for quantum technologies, enabling communication and computation tasks that surpass classical limits. Its distribution across networks is essential for interconnecting quantum processors, enabling distributed quantum computing to address complex challenges in areas such as drug discovery, material science, and optimization. In this work, we report the successful distribution of polarization-entangled photon pairs across a campus-scale, three-node qu…

Beyond Token Limits: Assessing Language Model Performance on Long Text Classification
Mikl\'os Seb\H{o}k, Viktor Kov\'acs, Martin B\'an\'oczy, Daniel M{\o}ller Eriksen, Nathalie Neptune, Philippe Roussille
https://arxiv.org/abs/2509.10199

Beyond Token Limits: Assessing Language Model Performance on Long Text Classification
The most widely used large language models in the social sciences (such as BERT, and its derivatives, e.g. RoBERTa) have a limitation on the input text length that they can process to produce predictions. This is a particularly pressing issue for some classification tasks, where the aim is to handle long input texts. One such area deals with laws and draft laws (bills), which can have a length of multiple hundred pages and, therefore, are not particularly amenable for processing with models tha…

Anthropic to debut new rate limits for Claude Pro and Max on Aug. 28, likely curbing <5% of users, saying some run Claude Code "continuously in the background" (Maxwell Zeff/TechCrunch)
https://techcrunch.com/2025/07/28/anthro…

Anthropic unveils new rate limits to curb Claude Code power users | TechCrunch
The new rate limits will go into effect August 28 for subscribers to Anthropic's $20-per-month Pro plan, as well as its $100- and $200-per-month Max plans.

Unveiling the link between quantum ghost imaging and Grover's quantum searching algorithm
Neelan Gounden, Fazilah Nothlawala, Paola C. Obando, Thomas Konrad, Andrew Forbes, Isaac Nape
https://arxiv.org/abs/2508.11296

Unveiling the link between quantum ghost imaging and Grover's quantum searching algorithm
Photonic quantum technologies have become pivotal in the implementation of communication, imaging and computing modalities. Among these applications, quantum ghost imaging (GI) exploits photon correlations to surpass classical limits, with recent advances in spatial-mode encoding and phase imaging. In parallel, all-optical computing offers powerful, passive-light processing capabilities. Here, we explore the intersection of these domains, revealing a conceptual and operational link between GI a…

Long-time storage of a decoherence-free subspace logical qubit in a dual-type quantum memory
Y. L. Xu, L. Zhang, C. Zhang, Y. K. Wu, Y. Y. Chen, C. X. Huang, Z. B. Cui, R. Yao, W. Q. Lian, J. Y. Ma, W. X. Guo, B. X. Qi, P. Y. Hou, Y. F. Pu, Z. C. Zhou, L. He, L. M. Duan
https://arxiv.org/abs/2507.13320

Long-time storage of a decoherence-free subspace logical qubit in a dual-type quantum memory
A quantum memory is an essential element for quantum computation, quantum network and quantum metrology. Previously, a single-qubit quantum memory with a coherence time of about an hour has been realized in a dual-species setup where a coolant ion provides sympathetic cooling for a memory ion of different species. However, the frequent random position hopping between the ions in the room-temperature trap limits the technique there only applicable to single-qubit storage. Here we report a multi-…

Saturable Quantum Speed Limits for Imaginary-Time Evolution
Kohei Kobayashi
https://arxiv.org/abs/2508.10361 https://arxiv.org/pdf/2508.10361

Saturable Quantum Speed Limits for Imaginary-Time Evolution
We derive a Geometric quantum speed limit (QSL) for imaginary-time evolution, where the dynamics is governed by a non-unitary Schrödinger equation. By introducing a cost function based on the angular distance between the normalized evolving state and the initial state, we obtain a lower bound on the evolution time expressed as the ratio between this angle and the time-averaged energy dispersion. Our bound is analytical, general, and applicable to arbitrary time-independent Hamiltonians. We ana…