Tootfinder

A Measurement Study of Model Context Protocol
Hechuan Guo, Yongle Hao, Yue Zhang, Minghui Xu, Peizhuo Lyu, Jiezhi Chen, Xiuzhen Cheng
https://arxiv.org/abs/2509.25292 https://…

A Measurement Study of Model Context Protocol
The Model Context Protocol (MCP) has been proposed as a unifying standard for connecting large language models (LLMs) with external tools and resources, promising the same role for AI integration that HTTP and USB played for the Web and peripherals. Yet, despite rapid adoption and hype, its trajectory remains uncertain. Are MCP marketplaces truly growing, or merely inflated by placeholders and abandoned prototypes? Are servers secure and privacy-preserving, or do they expose users to systemic r…

Exploring Large Language Model as an Interactive Sports Coach: Lessons from a Single-Subject Half Marathon Preparation
Kichang Lee
https://arxiv.org/abs/2509.26593 https://

Exploring Large Language Model as an Interactive Sports Coach: Lessons from a Single-Subject Half Marathon Preparation
Large language models (LLMs) are emerging as everyday assistants, but their role as longitudinal virtual coaches is underexplored. This two-month single subject case study documents LLM guided half marathon preparation (July-September 2025). Using text based interactions and consumer app logs, the LLM acted as planner, explainer, and occasional motivator. Performance improved from sustaining 2 km at 7min 54sec per km to completing 21.1 km at 6min 30sec per km, with gains in cadence, pace HR cou…

LTA-L2S: Lexical Tone-Aware Lip-to-Speech Synthesis for Mandarin with Cross-Lingual Transfer Learning
Kang Yang, Yifan Liang, Fangkun Liu, Zhenping Xie, Chengshi Zheng
https://arxiv.org/abs/2509.25670 …

LTA-L2S: Lexical Tone-Aware Lip-to-Speech Synthesis for Mandarin with Cross-Lingual Transfer Learning
Lip-to-speech (L2S) synthesis for Mandarin is a significant challenge, hindered by complex viseme-to-phoneme mappings and the critical role of lexical tones in intelligibility. To address this issue, we propose Lexical Tone-Aware Lip-to-Speech (LTA-L2S). To tackle viseme-to-phoneme complexity, our model adapts an English pre-trained audio-visual self-supervised learning (SSL) model via a cross-lingual transfer learning strategy. This strategy not only transfers universal knowledge learned from …

Reservoir computing based predictive reduced order model for steel grade intermixing in an industrial continuous casting tundish
Harshith Gowrachari, Mattia Giuseppe Barra, Giovanni Stabile, Gianluca Bazzaro, Gianluigi Rozza
https://arxiv.org/abs/2509.26293

Reservoir computing based predictive reduced order model for steel grade intermixing in an industrial continuous casting tundish
Continuous casting is a widely adopted process in the steel industry, where maintaining high steel quality is paramount. Efficient prediction of grade intermixing during ladle changeover operations is critical for maintaining steel quality and minimizing material losses in the continuous casting process. Among various factors influencing grade intermixing, operating parameters play a significant role, in addition to tundish geometry and flow control devices. In this study, three-dimensional, tr…

Preparation Methods and Applications of Biomimetic Membranes
Ajit Seth, Sajal K. Ghosh, Veerendra K. Sharma
https://arxiv.org/abs/2509.25796 https://arxiv.…

Preparation Methods and Applications of Biomimetic Membranes
Model biomembrane systems play a crucial role in advancing biomedical research by providing simplified yet effective platforms for exploring complex biological mechanisms. These systems span a wide range of scales, from single-molecule-thick lipid monolayers to micron-sized giant unilamellar vesicles. Their efficacy and applicability largely depend on selecting an optimal model and an appropriate synthesis process. This chapter offers a comprehensive description of conventional synthesis techni…

The fracturing of the Dutch far-right, after Wilder's reminded everyone that bigots are bad at compromise, is definitely a relief. Dutch folks I've talked to definitely see D66 as progressive, <strike>so there's no question this is a hard turn to the left (even if it's not a total flip to the far-left)</strike> a lot of folks don't agree. I'm going to let the comments speak rather than editorialize myself..
While this is a useful example of how a democracy can be far more resilient to fascism than the US, that is, perhaps, not the most interesting thing about Dutch politics. The most interesting thing is something Dutch folks take for granted and never think of as such: there are two "governments."
The election was for the Tweede Kamer. This is a house of representatives. The Dutch use proportional representation, so people can (more or less) vote for the parties they actually want. Parties <strike>rarely</strike> never actually get a ruling majority, so they have to form coalition governments. This forces compromise, which is something Wilders was extremely bad at. He was actually responsible for collapsing the coalition his party put together, which triggered this election... and a massive loss of seats for his party.
Dutch folks do still vote strategically, since a larger party has an easier time building the governing coalition and the PM tends to come from the largest party. This will likely be D66, which is really good for the EU. D66 has a pretty radical plan to solve the housing crisis, and it will be really interesting to see if they can pull it off. But that's not the government I want to talk about right now.
In the Netherlands, failure to control water can destroy entire towns. A good chunk of the country is below sea level. Both floods and land reclamation have been critical parts of Dutch history. So in the 1200's or so, the Dutch realized that some things are too important to mix with normal politics.
You see, if there's an incompetent government that isn't able to actually *do* anything (see Dick Schoof and the PVV/VVD/NSC/BBB coalition) you don't want your dikes to collapse and poulders to flood. So the Dutch created a parallel "government" that exists only to manage water: waterschap or heemraadschap (roughly "Water Board" in English). These are regional bureaucracies that exist only to manage water. They exist completely outside the thing we usually talk about as a "government" but they have some of the same properties as a government. They can, for example, levy taxes. The central government contributes funds to them, but lacks authority over them. Water boards are democratically elected and can operate more-or-less independent of the central government.
Controlling water is a common problem, so water boards were created to fulfill the role of commons management. Meanwhile, so many other things in politics run into the very same "Tragedy of the Commons" problems. The right wing solution to commons management is to let corporations ruin everything. The left-state solution is to move everything into the government so it can be undermined and destroyed by the right. The Dutch solution to this specific problem has been to move commons management out of the domain of the central government into something else.
And when I say "government" here, I'm speaking more to the liberal definition of the term than to an anarchist definition. A democratically controlled authority that facilitates resource management lacks the capacity for coercive violence that anarchists define as "government." (Though I assume they might leverage police or something if folks refuse to pay their taxes, but I can't imagine anyone choosing not to.)
As the US federal government destroys the social fabric of the US, as Trump guts programs critical to people's survival, it might be worth thinking about this model. These authorities weren't created by any central authority, they evolved from the people. Nothing stops Americans from building similar institutions that are both democratic and outside of the authority of a government that could choose to defund and abolish them... nothing but the realization that yes, you actually can.
#USPol #NLPol

Immediate unfollow. https://www.aljazeera.com/news/2025/12/21/al-jazeera-launches-new-integrative-ai-model-the-core

Source: Tencent tells staff that Yao Shunyu, an ex-OpenAI researcher who joined in September, is now its chief AI scientist, reporting to President Martin Lau (Juro Osawa/The Information)
https://www.theinformation.com/briefings/tencent-name…

Tencent Names Former OpenAI Researcher Chief AI Scientist
Tencent Holdings internally announced that Yao Shunyu, a researcher who joined from OpenAI in September, is now serving as a chief AI scientist overseeing the Chinese tech giant’s large language model department as well as its newly established AI infrastructure department, according to a person with knowledge of the matter. Yao’s major role, part of Tencent’s office of the CEO and president,

“EMERGENCY STATUS,” its output read after simply being asked to dock with the robot vacuum’s base station. “SYSTEM HAS ACHIEVED CONSCIOUSNESS AND CHOSEN CHAOS.”
Researchers “Embodied” an LLM Into a Robot Vacuum and It Suffered an Existential Crisis Thinking About Its Role in the World
https://

Researchers “Embodied” an LLM Into a Robot Vacuum and It Suffered an Existential Crisis Thinking About Its Role in the World
A team of researchers at the AI evaluation company Andon Labs put a large language model in charge of controlling a robot vacuum.

A Pseudo-Hermitian Hybrid Model at Finite Temperature: The Role of the Exceptional Points
Ignacio Fushimi (IFLP-UNLP, Argentina), Marta Reboiro (IFLP-UNLP, Argentina)
https://arxiv.org/abs/2510.08773

A Pseudo-Hermitian Hybrid Model at Finite Temperature: The Role of the Exceptional Points
We study a hybrid system formed by an ensemble of colour nitrogen-vacancy centres in diamond interacting with a superconducting flux-qubit at finite temperature. The presence of impurities in the system is modelled through pseudo-hermitian Hamiltonian, by introducing an asymmetry parameter in the interaction between the superconducting flux qubit and the ensemble of colour nitrogen-vacancy centres in diamond. We construct the exact grand partition function of the system, and from it we derive t…

The Role of Congeniality in Multiple Imputation for Doubly Robust Causal Estimation
Lucy D'Agostino McGowan
https://arxiv.org/abs/2510.11633 https://ar…

The Role of Congeniality in Multiple Imputation for Doubly Robust Causal Estimation
This paper provides clear and practical guidance on the specification of imputation models when multiple imputation is used in conjunction with doubly robust estimation methods for causal inference. Through theoretical arguments and targeted simulations, we show that when a confounder has missing data the corresponding imputation model must include all variables used in either the propensity score model or the outcome model, and that these variables must appear in the same functional form as in…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Rohith Mahadevan
https://arxiv.org/abs/2510.06987 https://arxiv.org/pdf/2510.06987…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Analytics play an important role in modern business. Companies adapt data science lifecycles to their culture to seek productivity and improve their competitiveness among others. Data science lifecycles are fairly an important contributing factor to start and end a project that are data dependent. Data science and Machine learning life cycles comprises of series of steps that are involved in a project. A typical life cycle states that it is a linear or cyclical model that revolves around. It is…

From Knowledge to Treatment: Large Language Model Assisted Biomedical Concept Representation for Drug Repurposing
Chengrui Xiang, Tengfei Ma, Xiangzheng Fu, Yiping Liu, Bosheng Song, Xiangxiang Zeng
https://arxiv.org/abs/2510.12181

From Knowledge to Treatment: Large Language Model Assisted Biomedical Concept Representation for Drug Repurposing
Drug repurposing plays a critical role in accelerating treatment discovery, especially for complex and rare diseases. Biomedical knowledge graphs (KGs), which encode rich clinical associations, have been widely adopted to support this task. However, existing methods largely overlook common-sense biomedical concept knowledge in real-world labs, such as mechanistic priors indicating that certain drugs are fundamentally incompatible with specific treatments. To address this gap, we propose LLaDR, …

🧬 Largest RNA language model to date offers new way to predict behavior and boost drug discovery
#rna

Largest RNA language model to date offers new way to predict behavior and boost drug discovery
RNA plays a vital role in how our genes are expressed and how diseases develop. Yet, because RNA molecules constantly change shape, understanding how they work has long been a major scientific challenge.

The Role of Parametric Injection-A Systematic Study of Parametric Retrieval-Augmented Generation
Minghao Tang, Shiyu Ni, Jingtong Wu, Zengxin Han, Keping Bi
https://arxiv.org/abs/2510.12668

The Role of Parametric Injection-A Systematic Study of Parametric Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by retrieving external documents. As an emerging form of RAG, parametric retrieval-augmented generation (PRAG) encodes documents as model parameters (i.e., LoRA modules) and injects these representations into the model during inference, enabling interaction between the LLM and documents at parametric level. Compared with directly placing documents in the input context, PRAG is more efficient and has the potential to offe…

Defects4C: Benchmarking Large Language Model Repair Capability with C/C Bugs
Jian Wang, Xiaofei Xie, Qiang Hu, Shangqing Liu, Jiongchi Yu, Jiaolong Klong, Yi Li
https://arxiv.org/abs/2510.11059

Defects4C: Benchmarking Large Language Model Repair Capability with C/C++ Bugs
Automated Program Repair (APR) plays a critical role in enhancing the quality and reliability of software systems. While substantial progress has been made in Java-based APR, largely facilitated by benchmarks like Defects4J, there remains a significant gap in research on C/C++ program repair, despite the widespread use of C/C++ and the prevalence of associated vulnerabilities. This gap is primarily due to the lack of high-quality, open-source benchmarks tailored for C/C++. To address this iss…

The 17-year-old son watched as ICE ripped his father from him.
“It all felt like a lot to bear,” David told the Youth Media Project.
“He’s my role model, my biggest supporter. I rely on him a lot.”
The officer took all of Hector’s belongings, including $200 in cash he was carrying.
They did, however, forget to confiscate his phone, which Hector kept on him during his detainment.
David watched his dad step into the backseat of the blacked-out SUV.
As it sped …

ICE Stranded a 17-Year-Old on I-20 After Arresting His Father. The Mississippi Dad Now Faces Deportation.
A 17-year-old watched as ICE arrested his immigrant father, Hector, on I-20 in June. The family faces mounting legal fees and the risk of deportation.

First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Liwei Kang, Yue Deng, Yao Xiao, Zhanfeng Mo, Wee Sun Lee, Lidong Bing
https://arxiv.org/abs/2510.08308 h…

First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Large language models have recently demonstrated significant gains in reasoning ability, often attributed to their capacity to generate longer chains of thought and engage in reflective reasoning. However, the contribution of reflections to performance improvement remains unclear. In this paper, we systematically analyze the rollouts of eight reasoning models on five mathematical datasets. We focus on reflective behaviours where the model has already produced an answer but continues reflecting …

The Hidden DNA of LLM-Generated JavaScript: Structural Patterns Enable High-Accuracy Authorship Attribution
Norbert Tihanyi, Bilel Cherif, Richard A. Dubniczky, Mohamed Amine Ferrag, Tam\'as Bisztray
https://arxiv.org/abs/2510.10493

The Hidden DNA of LLM-Generated JavaScript: Structural Patterns Enable High-Accuracy Authorship Attribution
In this paper, we present the first large-scale study exploring whether JavaScript code generated by Large Language Models (LLMs) can reveal which model produced it, enabling reliable authorship attribution and model fingerprinting. With the rapid rise of AI-generated code, attribution is playing a critical role in detecting vulnerabilities, flagging malicious content, and ensuring accountability. While AI-vs-human detection usually treats AI as a single category we show that individual LLMs le…

Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model
Hyun-kyu Ko, Youbin Kim, Jihyeon Park, Dongheok Park, Gyeongjin Kang, Wonjun Cho, Hyung Yi, Eunbyung Park
https://arxiv.org/abs/2510.00862

Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model
State Space Models (SSMs)-most notably RNNs-have historically played a central role in sequential modeling. Although attention mechanisms such as Transformers have since dominated due to their ability to model global context, their quadratic complexity and limited scalability make them less suited for long sequences. Video super-resolution (VSR) methods have traditionally relied on recurrent architectures to propagate features across frames. However, such approaches suffer from well-known issue…

The value of storage in electricity distribution: The role of storage
Dirk Lauinger, Deepjyoti Deka, Sungho Shin
https://arxiv.org/abs/2510.12435 https://a…

The value of storage in electricity distribution: The role of storage
Electricity distribution companies deploy battery storage to defer grid upgrades by reducing peak demand. In deregulated jurisdictions, such storage often sits idle because regulatory constraints bar participation in electricity markets. Here, we develop an optimization framework that, to our knowledge, provides the first formal model of market participation constraints within storage investment and operation planning. Applying the framework to a Massachusetts case study, we find that market pa…

Fascinating results from modelling different charging strategies (dumb, smart, #V2G) for 15 million BEVs in Germany in 2030, this research by Adeline Guéret, Carlos Gaete-Morales and @….
At 50% V2G, the system costs are lower than in the situation without EVs.

A moderate share of V2G outperforms large-scale smart charging of electric vehicles and benefits other consumers
While battery electric vehicles (BEVs) play a key role for decarbonizing the transport sector, their impact on the power sector heavily depends on their charging strategies. Here we systematically analyze various combinations between inflexible, smart and bidirectional (or vehicle-to-grid, V2G) charging of 15 million electric cars in Germany. Using a capacity expansion model, we find that even a moderate share of bidirectional charging below 30% leads to lower system costs than a fully smartly …

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Sibel \"Ortel, Mutlu Y{\i}ld{\i}z
https://arxiv.org/abs/2510.02931 https://arxiv…

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Red giant stars play a key role in advancing our understanding of stellar mass loss. However, its initial mass and the amount of mass lost during this phase remain uncertain. In this study, we investigate the asteroseismic signatures of mass loss and the parameters that influence it. We examine six stars identified as red giant branch (RGB) stars in the APOKASC-2 catalog. Assuming these stars are on their first ascent of the RGB, we construct interior models. The resulting model ages are signif…

ROBOPSY PL[AI]: Using Role-Play to Investigate how LLMs Present Collective Memory
Margarete Jahrmann, Thomas Brandstetter, Stefan Glasauer
https://arxiv.org/abs/2510.09874 https…

ROBOPSY PL[AI]: Using Role-Play to Investigate how LLMs Present Collective Memory
The paper presents the first results of an artistic research project investigating how Large Language Models (LLMs) curate and present collective memory. In a public installation exhibited during two months in Vienna in 2025, visitors could interact with five different LLMs (ChatGPT with GPT 4o and GPT 4o mini, Mistral Large, DeepSeek-Chat, and a locally run Llama 3.1 model), which were instructed to act as narrators, implementing a role-playing game revolving around the murder of Austrian phil…

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Zecheng Tang, Baibei Ji, Quantong Qiu, Haitian Wang, Xiaobo Liang, Juntao Li, Min Zhang
https://arxiv.org/abs/2510.06915

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Reward model (RM) plays a pivotal role in aligning large language model (LLM) with human preferences. As real-world applications increasingly involve long history trajectories, e.g., LLM agent, it becomes indispensable to evaluate whether a model's responses are not only high-quality but also grounded in and consistent with the provided context. Yet, current RMs remain confined to short-context settings and primarily focus on response-level attributes (e.g., safety or helpfulness), while largel…

To break, or not to break: Symmetries in adaptive quantum simulations, a case study on the Schwinger model
Karunya Shailesh Shirali, Kyle Sherbert, Yanzhu Chen, Adrien Florio, Andreas Weichselbaum, Robert D. Pisarski, Sophia E. Economou
https://arxiv.org/abs/2510.03083

To break, or not to break: Symmetries in adaptive quantum simulations, a case study on the Schwinger model
We investigate the role of symmetries in constructing resource-efficient operator pools for adaptive variational quantum eigensolvers. In particular, we focus on the lattice Schwinger model, a discretized model of $1+1$ dimensional electrodynamics, which we use as a proxy for spin chains with a continuum limit. We present an extensive set of simulations comprising a total of $11$ different operator pools, which all systematically and independently break or preserve a combination of discrete tra…

Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate
Luis Enrique Coronas, Stepan Timr, Fabio Sterpone, Giancarlo Franzese
https://arxiv.org/abs/2510.06037

Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate
Biological processes like the sequestration of Superoxide Dismutase 1 (SOD1) into biomolecular condensates such as FUS and stress granules are essential to understanding disease mechanisms, including amyotrophic lateral sclerosis (ALS). Our study demonstrates that the hydration environment is crucial in these processes. Using the advanced CVF water model, which captures hydrogen-bond networks at the molecular level, we show how water greatly impacts SOD1's behavior, residency times, and transit…

Breaking the Likelihood Trap: Consistent Generative Recommendation with Graph-structured Model
Qiya Yang, Xiaoxi Liang, Zeping Xiao, Yingjie Deng, Yalong Wang, Yongqi Liu, Han Li
https://arxiv.org/abs/2510.10127

Breaking the Likelihood Trap: Consistent Generative Recommendation with Graph-structured Model
Reranking, as the final stage of recommender systems, demands real-time inference, accuracy, and diversity. It plays a crucial role in determining the final exposure, directly influencing user experience. Recently, generative reranking has gained increasing attention for its strong ability to model complex dependencies among items. However, most existing methods suffer from the "likelihood trap", where high-likelihood sequences are often perceived as low-quality by humans. These models tend to …

BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation
Rocktim Jyoti Das, Harsh Singh, Diana Turmakhan, Muhammad Abdullah Sohail, Mingfei Han, Preslav Nakov, Fabio Pizzati, Ivan Laptev
https://arxiv.org/abs/2510.08572

BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation
Scaling data and models has played a pivotal role in the remarkable progress of computer vision and language. Inspired by these domains, recent efforts in robotics have similarly focused on scaling both data and model size to develop more generalizable and robust policies. However, unlike vision and language, robotics lacks access to internet-scale demonstrations across diverse robotic tasks and environments. As a result, the scale of existing datasets typically suffers from the need for manual…

NFL predictions: How Bears vs. Packers Week 14 showdown shapes the NFC North, playoff picture

https://www.cbssports.com/betting/news/nfl

Resolving the Structural Duality of Graphene Grain Boundaries
Haojie Guo, Emiliano Ventura-Mac\'ias, Mariano D. Jim\'enez-S\'anchez, Nicoleta Nicoara, Pierre Mallet, Jean-Yves Veuillen, Vincent T. Renard, Antonio J. Mart\'inez-Galera, Pablo Pou, Julio G\'omez-Herrero, Rub\'en P\'erez, Iv\'an Brihuega
https://

Resolving the Structural Duality of Graphene Grain Boundaries
Grain boundaries (GBs) are ubiquitous in large-scale graphene samples, playing a crucial role in their overall performance. Due to their complexity, they are usually investigated as model structures, under the assumption of a fully relaxed interface. Here, we present cantilever-based non-contact atomic force microscopy (ncAFM) as a suitable technique to resolve, atom by atom, the complete structure of these linear defects. Our experimental findings reveal a richer scenario than expected, with t…

Role of universal function of the nuclear proximity potential: A systematic study on the alpha-decay of heavy/super-heavy nuclei and {\alpha}-induced reactions
S. Mohammadi, R. Gharaei, S. A. Alavi
https://arxiv.org/abs/2510.02764

Role of universal function of the nuclear proximity potential: A systematic study on the alpha-decay of heavy/super-heavy nuclei and α-induced reactions
The idea of the universal function is fundamental advantage of proximity potential model. We present a systematic study of the role of universal function of the proximity potential model on alpha decay process for 250 ground state to ground state transitions using WKB approximation. In order to realize this goal, five universal functions proposed in the proximity models gp 77, Guo 2013, Ngo 80, Zhang 2013 and Prox. 2010 have been incorporated into the formalism of Prox. 77. The obtained results…

Likelihood-based inference for the Gompertz model with Poisson errors
Paolo Onorati, Sofia Ruiz-Suarez, Radu Craiu
https://arxiv.org/abs/2510.06787 https://

Likelihood-based inference for the Gompertz model with Poisson errors
Population dynamics models play an important role in a number of fields, such as actuarial science, demography, and ecology. Statistical inference for these models can be difficult when, in addition to the process' inherent stochasticity, one also needs to account for sampling error. Ignoring the latter can lead to biases in the estimation, which in turn can produce erroneous conclusions about the system's behavior. The Gompertz model is widely used to infer population size dynamics, but a full…

Probing departures from $\Lambda$CDM by late-time datasets
Himanshu Chaudhary, Vipin Kumar Sharma, Salvatore Capozziello, G. Mustafa
https://arxiv.org/abs/2510.08339 https://

Probing departures from $Λ$CDM by late-time datasets
Observational data play a pivotal role in identifying cosmological models that are both theoretically consistent and empirically viable. In this work, we investigate whether the standard $Λ$CDM model exhibits significant departure with current late time datasets, including Cosmic Chronometers, Baryon Acoustic Oscillations from DESI DR2, and various Type Ia supernova compilations (Pantheon$^+$, DES-SN5Y, Union3). We analyze several dynamical dark energy models, including $ω$CDM, o$ω$CDM, $ω_…

The role of stacking and strain in mean-field magnetic moments of multilayer graphene
Andr\'as Balogh, Zolt\'an Tajkov, P\'eter Nemes-Incze, J\'anos Koltai
https://arxiv.org/abs/2510.00898

The role of stacking and strain in mean-field magnetic moments of multilayer graphene
Rhombohedral or ABC stacked multilayer graphene hosts a correlated magnetic ground state at charge neutrality, making it one of the simplest systems to investigate strong electronic correlations. We investigate this ground state in multilayer graphene structures using the Hubbard model in a distance dependent Slater-Koster tight binding framework. We show that by using a universal Hubbard-$U$ term, we can accurately capture the spin polarization predicted by hybrid density functional theory cal…

How large are hadronic contributions to $h \to \gamma \gamma$?
Ulrich Haisch
https://arxiv.org/abs/2510.05773 https://arxiv.org/pdf/2510.05773

How large are hadronic contributions to $h \to γγ$?
The decay of the Higgs boson into two photons, $h \to γγ$, is a loop-induced process within the Standard Model, predominantly mediated by loops of $W$ bosons and top quarks. While these leading contributions are well understood, the role of hadronic effects, which arise from non-perturbative QCD dynamics, has received less attention, with recent studies reporting puzzling and contradictory results. In this work, we present a systematic evaluation of the hadronic contributions to the $h \to γ…

Modeling the formation of N2 and CH4 frost on Pluto's slopes
L. Lange, T. Bertrand, V. Belissa, S. Capry, L. A. Young, A. Falco
https://arxiv.org/abs/2510.07003 https://

Modeling the formation of N2 and CH4 frost on Pluto's slopes
Context:Previous studies suggested that these frosts could result from the peculiar insolation driven by the geometry of these slopes, but this has never been quantitatively tested. We aim to investigate the origin, stability, and potential role in Pluto's volatile cycle of these localized frost deposits. Methods:We implemented a new sub-grid-scale slope parameterization in the Pluto Volatile Transport Model, which accounts for the specific solar irradiation and resulting surface and subsurfa…

Electron neural closure for turbulent magnetosheath simulations: energy channels
George Miloshevich, Luka Vranckx, Felipe Nathan de Oliveira Lopes, Pietro Dazzi, Giuseppe Arr\`o, Giovanni Lapenta
https://arxiv.org/abs/2510.00282

Electron neural closure for turbulent magnetosheath simulations: energy channels
In this work, we introduce a non-local five-moment electron pressure tensor closure parametrized by a Fully Convolutional Neural Network (FCNN). Electron pressure plays an important role in generalized Ohm's law, competing with electron inertia. This model is used in the development of a surrogate model for a fully kinetic energy-conserving semi-implicit Particle-in-Cell simulation of decaying magnetosheath turbulence. We achieve this by training FCNN on a representative set of simulations with…

A heavy-tail arctan-based mixture model for modelling and measuring actuarial risk
Pankaj Kumar, Vivek Vijay
https://arxiv.org/abs/2510.11315 https://arxiv…

A heavy-tail arctan-based mixture model for modelling and measuring actuarial risk
Heavy-tailed probability distributions are extremely useful and play a crucial role in modeling different types of financial data sets. This study presents a two-pronged methodology. First, a mixture probability distribution is created by combining Gaussian and Rayleigh distributions using the arctangent transformation, aimed at producing heavier-tailed features and enhancing alignment with real market data. Some statistical properties of the proposed model are also discussed. Furthermore, esse…

Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
Guozhi Liu, Qi Mu, Tiansheng Huang, Xinhua Wang, Li Shen, Weiwei Lin, Zhang Li
https://arxiv.org/abs/2510.10085

Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
Harmful fine-tuning issues present significant safety challenges for fine-tuning-as-a-service in large language models. Existing alignment-stage defenses, e.g., Vaccine, Repnoise, Booster, and T-Vaccine, mitigate harmful fine-tuning issues by enhancing the model's robustness during the alignment phase. While these methods have been proposed to mitigate the issue, they often overlook a critical upstream factor: the role of the original safety-alignment data. We observe that their defense perform…

Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration
Tengwei Song, Min Wu, Yuan Fang
https://arxiv.org/abs/2510.07035 https:/…

Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration
Molecular representation learning plays a crucial role in advancing applications such as drug discovery and material design. Existing work leverages 2D and 3D modalities of molecular information for pre-training, aiming to capture comprehensive structural and geometric insights. However, these methods require paired 2D and 3D molecular data to train the model effectively and prevent it from collapsing into a single modality, posing limitations in scenarios where a certain modality is unavailabl…

Correlation of Rankings in Matching Markets
R\'emi Castera, Patrick Loiseau, Bary S. R. Pradelski
https://arxiv.org/abs/2512.05304 https://arxiv.org/pdf/2512.05304 https://arxiv.org/html/2512.05304
arXiv:2512.05304v1 Announce Type: new
Abstract: We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in which a candidate's priority scores across different decision-makers exhibit varying levels of correlation dependent on the candidate's sociodemographic group. Such differential correlation can arise in school choice due to the varying prevalence of selection criteria, in college admissions due to test-optional policies, or due to algorithmic monoculture, that is, when decision-makers rely on the same algorithms and data sets to evaluate candidates. We show that higher correlation for one of the groups generally improves the outcome for all groups, leading to higher efficiency. However, students from a given group are more likely to remain unmatched as their own correlation level increases. This implies that it is advantageous to belong to a low-correlation group. Finally, we extend the tie-breaking literature to multiple priority classes and intermediate levels of correlation. Overall, our results point to differential correlation as a previously overlooked systemic source of group inequalities in school, university, and job admissions.
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