Tootfinder

Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
Peter Shaw, James Cohan, Jacob Eisenstein, Kristina Toutanova
https://arxiv.org/abs/2509.22445

Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
The Minimum Description Length (MDL) principle offers a formal framework for applying Occam's razor in machine learning. However, its application to neural networks such as Transformers is challenging due to the lack of a principled, universal measure for model complexity. This paper introduces the theoretical notion of asymptotically optimal description length objectives, grounded in the theory of Kolmogorov complexity. We establish that a minimizer of such an objective achieves optimal compre…

🚨Job alert! 🚨 Two Post-docs "bridging knowledge between Earth and Planetary sciences (the Solar System) and Exoplanet science (beyond the Solar System)" at the Munich Center for Geoastronomy #geology #planetary

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
Karim Khamaisi, Oliver Kamer, Bruno Rodrigues, Jan von der Assen, Burkhard Stiller
https://arxiv.org/abs/2509.22568

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
During large-scale crises disrupting cellular and Internet infrastructure, civilians lack reliable methods for communication, aid coordination, and access to trustworthy information. This paper presents a unified emergency communication system integrating a low-power, long-range network with a crisis-oriented smartphone application, enabling decentralized and off-grid civilian communication. Unlike previous solutions separating physical layer resilience from user layer usability, our design mer…

JointDiff: Bridging Continuous and Discrete in Multi-Agent Trajectory Generation
Guillem Capellera, Luis Ferraz, Antonio Rubio, Alexandre Alahi, Antonio Agudo
https://arxiv.org/abs/2509.22522

JointDiff: Bridging Continuous and Discrete in Multi-Agent Trajectory Generation
Generative models often treat continuous data and discrete events as separate processes, creating a gap in modeling complex systems where they interact synchronously. To bridge this gap, we introduce JointDiff, a novel diffusion framework designed to unify these two processes by simultaneously generating continuous spatio-temporal data and synchronous discrete events. We demonstrate its efficacy in the sports domain by simultaneously modeling multi-agent trajectories and key possession events. …

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[9/12]:
- Bridging Fairness and Explainability: Can Input-Based Explanations Promote Fairness in Hate Speec...
Yifan Wang, Mayank Jobanputra, Ji-Ung Lee, Soyoung Oh, Isabel Valera, Vera Demberg

⛐ Bridging Vision, Language, and Mathematics: Pictographic Character Reconstruction with Bézier Curves
#cs

Bridging Vision, Language, and Mathematics: Pictographic Character Reconstruction with Bézier Curves
While Vision-language Models (VLMs) have demonstrated strong semantic capabilities, their ability to interpret the underlying geometric structure of visual information is less explored. Pictographic characters, which combine visual form with symbolic structure, provide an ideal test case for this capability. We formulate this visual recognition challenge in the mathematical domain, where each character is represented by an executable program of geometric primitives. This is framed as a program …

Bridging continents through connectivity 🌍
Through the GÉANT Twinning Programme, a collaboration between Jisc and KENET brought #eduroam to one of Kenya’s most remote research sites—proving how global NREN partnerships can transform access to connectivity.
🔗 Read the full story, detailed results, and reflections from Peter Kent (Jisc):

Bitcoin bridging app Garden Finance Reportedly Loses Over $10.8 Million in Hacking Incident
https://beincrypto.com/bitcoin-bridging-app-garden-finance-hack/

Garden Finance Reportedly Loses Over $10.8 Million in Hacking Incident
Garden Finance hack leads to $10.8 million loss after money laundering claims, echoing crypto’s ongoing security struggles.

First PROPL 2025 talk: Bridging disciplinary gaps in climate research.
Presented by Christian Urlea.
#icfpsplash25

The Colorful Cultures of Pre-Colonial Mindanao
Bridging the gap between what seems like ‘exotic’ Mindanao starts with understanding the culture of its people
https://www.esquiremag.ph/long-reads/features/mindano-culture-a2212-20200313-lfrm

Diffusion-Link: Diffusion Probabilistic Model for Bridging the Audio-Text Modality Gap
KiHyun Nam, Jongmin Choi, Hyeongkeun Lee, Jungwoo Heo, Joon Son Chung
https://arxiv.org/abs/2510.11330

Diffusion-Link: Diffusion Probabilistic Model for Bridging the Audio-Text Modality Gap
Contrastive audio-language pretraining yields powerful joint representations, yet a persistent audio-text modality gap limits the benefits of coupling multimodal encoders with large language models (LLMs). We present Diffusion-Link, a diffusion-based modality-bridging module that generatively maps audio embeddings into the text-embedding distribution. The module is trained at the output embedding from the frozen multimodal encoder and implemented as a lightweight network with three residual MLP…

Bridging Semantics & Structure for Software Vulnerability Detection using Hybrid Network Models
Jugal Gajjar, Kaustik Ranaware, Kamalasankari Subramaniakuppusamy
https://arxiv.org/abs/2510.10321

Bridging Semantics & Structure for Software Vulnerability Detection using Hybrid Network Models
Software vulnerabilities remain a persistent risk, yet static and dynamic analyses often overlook structural dependencies that shape insecure behaviors. Viewing programs as heterogeneous graphs, we capture control- and data-flow relations as complex interaction networks. Our hybrid framework combines these graph representations with light-weight (<4B) local LLMs, uniting topological features with semantic reasoning while avoiding the cost and privacy concerns of large cloud models. Evaluated on…

Bridging Research and Practice in Simulation-based Testing of Industrial Robot Navigation Systems
Sajad Khatiri, Francisco Eli Vina Barrientos, Maximilian Wulf, Paolo Tonella, Sebastiano Panichella
https://arxiv.org/abs/2510.09396

Bridging Research and Practice in Simulation-based Testing of Industrial Robot Navigation Systems
Ensuring robust robotic navigation in dynamic environments is a key challenge, as traditional testing methods often struggle to cover the full spectrum of operational requirements. This paper presents the industrial adoption of Surrealist, a simulation-based test generation framework originally for UAVs, now applied to the ANYmal quadrupedal robot for industrial inspection. Our method uses a search-based algorithm to automatically generate challenging obstacle avoidance scenarios, uncovering fa…

Roadmap: Emerging Platforms and Applications of Optical Frequency Combs and Dissipative Solitons
Dmitry Skryabin, Arne Kordts, Richard Zeltner, Ronald Holzwarth, Victor Torres-Company, Tobias Herr, Fuchuan Lei, Qi-Fan Yang, Camille-Sophie Br\`es, John F. Donegan, Hai-Zhong Weng, Delphine Marris-Morini, Adel Bousseksou, Markku Vainio, Thomas Bunel, Matteo Conforti, Arnaud Mussot, Erwan Lucas, Julien Fatome, Yuk Shan Cheng, Derryck T. Reid, Alessia Pasquazi, Marco Peccianti, M. Giudici, M. Marconi, A. Bartolo, N. Vigne, B. Chomet, A. Garnache, G. Beaudoin, I. Sagnes, Richard Burguete, Sarah Hammer, Jonathan Silver
https://arxiv.org/abs/2511.18231 https://arxiv.org/pdf/2511.18231 https://arxiv.org/html/2511.18231
arXiv:2511.18231v1 Announce Type: new
Abstract: The discovery of optical frequency combs (OFCs) has revolutionised science and technology by bridging electronics and photonics, driving major advances in precision measurements, atomic clocks, spectroscopy, telecommunications, and astronomy. However, current OFC systems still require further development to enable broader adoption in fields such as communication, aerospace, defence, and healthcare. There is a growing need for compact, portable OFCs that deliver high output power, robust self-referencing, and application-specific spectral coverage. On the conceptual side, progress toward such systems is hindered by an incomplete understanding of the fundamental principles governing OFC generation in emerging devices and materials, as well as evolving insights into the interplay between soliton and mode-locking effects. This roadmap presents the vision of a diverse group of academic and industry researchers and educators from Europe, along with their collaborators, on the current status and future directions of OFC science. It highlights a multidisciplinary approach that integrates novel physics, engineering innovation, and advanced researcher training. Topics include advances in soliton science as it relates to OFCs, the extension of OFC spectra into the visible and mid-infrared ranges, metrology applications and noise performance of integrated OFC sources, new fibre-based OFC modules, OFC lasers and OFC applications in astronomy.
toXiv_bot_toot

Hey Bluesky users, I see your responses, but since you’re not bridging, I can't interact with you.
If you use this (https://fed.brid.gy/) then I could interact and reply. Cheers :)

Bridgy Fed
Bridgy Fed is a bridge between decentralized social networks like the fediverse, Bluesky, and web sites and blogs.

LI.FI, which provides businesses with price comparisons of crypto exchange rates and bridging fees, raised $29M, bringing its total funding to ~$52M (Carlos Garcia/Fortune)
https://fortune.com/2025/12/11/exclusive-crypto-startup-li-fi-raises-29-million/

Exclusive: Crypto startup LI.FI raises $29 million for cross-blockchain price discovery tool
The company aims to make moving across blockchains more efficient.

Uhm, no thank you, I don't think I'll bother with that "bridging" to "bluesky" that you want me to do.

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Dylan Hirsch, Jaime Fern\'andez Fisac, Sylvia Herbert
https://arxiv.org/abs/2510.09929

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Control barrier functions (CBFs) and Hamilton-Jacobi reachability (HJR) are central frameworks in safe control. Traditionally, these frameworks have been viewed as distinct, with the former focusing on optimally safe controller design and the latter providing sufficient conditions for safety. A previous work introduced the notion of a control barrier value function (CB-VF), which is defined similarly to the other value functions studied in HJR but has certain CBF-like properties. In this work, …

"Demokratische Kultur entsteht durch Übung. Jedes Gespräch, das von aufmerksamem Zuhören und aufrichtigem Sprechen geprägt ist, ist ein kleiner Schritt hin zu einer menschlicheren, inklusiveren und effektiveren Demokratie."
Josef Merk
#SprechenUndZuhören
#DemokratieStärken

Bridging Political Divides Through Democratic Dialogue: The »Speaking & Listening« Approach in Germany — Democracy & Belonging Forum
It is important to oppose authoritarian populism with fact-checking and critique, but we believe it is also crucial to pursue a positive, alternative vision. For us, this vision is an embodiment of democratic values, best expressed by the narrative: “Even when I strongly disagree with your opinion,

More bridging ligands activate direct exchange: the case of anisotropic Kitaev effective magnetic interactions
Pritam Bhattacharyya, Nikolay A. Bogdanov, Liviu Hozoi
https://arxiv.org/abs/2510.04149

More bridging ligands activate direct exchange: the case of anisotropic Kitaev effective magnetic interactions
A magnet is a collection of magnetic moments. How those interact is determined by what lies in between. In transition-metal and rare-earth magnetic compounds, the configuration of the ligands around each magnetic center and the connectivity of the ligand cages are therefore pivotal -- for example, the mutual interaction of magnetic species connected through one single ligand is qualitatively different from the case of two bridging anions. Two bridging ligands are encountered in Kitaev magnets. …

Bridging Caribbean Literature and Digital Humanities https://call-for-papers.sas.upenn.edu/cfp/2025/10/01/bridging-caribbean-literature-and-digital-humanities

Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Yinuo Zhang, Demao Liu, Zhichao Liang, Jiani Cheng, Kexin Lou, Jinqiao Duan, Ting Gao, Bin Hu, Quanying Liu
https://arxiv.org/abs/2510.10308

Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Recent breakthroughs in artificial intelligence (AI) are reshaping the way we construct computational counterparts of the brain, giving rise to a new class of ``surrogate brains''. In contrast to conventional hypothesis-driven biophysical models, the AI-based surrogate brain encompasses a broad spectrum of data-driven approaches to solve the inverse problem, with the primary objective of accurately predicting future whole-brain dynamics with historical data. Here, we introduce a unified framewo…

Bridging the Gap: Enhancing Gaze-Performance Link in Children with ASD through Dual-Level Visual Guidance in MR-DMT
Weiying Liu, Yanran Yuan, Zhiqiang Sheng, Dandan Lian, Sheng Li, Yufan Zhang, Yulong Bian, Juan Liu
https://arxiv.org/abs/2510.03724

Bridging the Gap: Enhancing Gaze-Performance Link in Children with ASD through Dual-Level Visual Guidance in MR-DMT
Autism Spectrum Disorder (ASD) is marked by action imitation deficits stemming from visuomotor integration impairments, posing challenges to imitation-based learning, such as dance movement therapy in mixed reality (MR-DMT). Previous gaze-guiding interventions in ASD have mainly focused on optimizing gaze in isolation, neglecting the crucial "gaze-performance link". This study investigates enhancing this link in MR-DMT for children with ASD. Initially, we experimentally confirmed the weak link:…

@… Hi, have you thought of bridging your Bluesky account here? Just follow @ap.brid.gy over there!

Agora: Bridging the GPU Cloud Resource-Price Disconnect
Ian McDougall, Noah Scott, Joon Huh, Kirthevasan Kandasamy, Karthikeyan Sankaralingam
https://arxiv.org/abs/2510.05111 ht…

Agora: Bridging the GPU Cloud Resource-Price Disconnect
The historic trend of Moore's Law, which predicted exponential growth in computational performance per dollar, has diverged for modern Graphics Processing Units (GPUs). While Floating Point Operations per Second (FLOPs) capabilities have continued to scale economically, memory bandwidth has not, creating a significant price-performance disconnect. This paper argues that the prevailing time-based pricing models for cloud GPUs are economically inefficient for bandwidth-bound workloads. These mode…

Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Abdur Rehman Anwar Qureshi, Adrian Rebmann, Timotheus Kampik, Matthias Weidlich, Mathias Weske
https://arxiv.org/abs/2510.06414

Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Business process management is increasingly practiced using data-driven approaches. Still, classical imperative process models, which are typically formalized using Petri nets, are not straightforwardly applicable to the relational databases that contain much of the available structured process execution data. This creates a gap between the traditional world of process modeling and recent developments around data-driven process analysis, ultimately leading to the under-utilization of often read…

We are happy to welcome @… from RWTH in today's #nfdicore playground talking about "Bridging the Gap from Biomedical to Domain-Agnostic Semantics".
Besides others, he is demonstrating that our

MCMC: Bridging Rendering, Optimization and Generative AI
Gurprit Singh, Wenzel Jakob
https://arxiv.org/abs/2510.09078 https://arxiv.org/pdf/2510.09078

MCMC: Bridging Rendering, Optimization and Generative AI
Generative artificial intelligence (AI) has made unprecedented advances in vision language models over the past two years. During the generative process, new samples (images) are generated from an unknown high-dimensional distribution. Markov Chain Monte Carlo (MCMC) methods are particularly effective in drawing samples from such complex, high-dimensional distributions. This makes MCMC methods an integral component for models like EBMs, ensuring accurate sample generation. Gradient-based opti…

Bridging the Prediction Error Method and Subspace Identification: A Weighted Null Space Fitting Method
Jiabao He, S. Joe Qin, H\r{a}kan Hjalmarsson
https://arxiv.org/abs/2510.02529

Bridging the Prediction Error Method and Subspace Identification: A Weighted Null Space Fitting Method
Subspace identification methods (SIMs) have proven to be very useful and numerically robust for building state-space models. While most SIMs are consistent, few if any can achieve the efficiency of the maximum likelihood estimate (MLE). Conversely, the prediction error method (PEM) with a quadratic criteria is equivalent to MLE, but it comes with non-convex optimization problems and requires good initialization points. This contribution proposes a weighted null space fitting (WNSF) approach for…

A class of graphs: Bridging structures in commutative algebra
Fahimeh Khosh-Ahang Ghasr
https://arxiv.org/abs/2510.06729 https://arxiv.org/pdf/2510.06729…

A class of graphs: Bridging structures in commutative algebra
We characterize classes of simplicial complexes $Δ$ for which the generators of the determinantal facet ideal $J_Δ$ form a reduced Gröbner basis. This result provides a new proof for a known fact about determinantal ideals in a special case and extends several existing results concerning binomial edge ideals and determinantal facet ideals. We also introduce and examine generalizations of interval graphs and proper interval graphs, aiming to establish equivalent characterizations for these …

Bridging the Synthesizability Gap in Perovskites by Combining Computations, Literature Data, and PU Learning
Rushik Desai, Junyeong Ahn, Alejandro Strachan, Arun Mannodi-Kanakkithodi
https://arxiv.org/abs/2510.06166

Bridging the Synthesizability Gap in Perovskites by Combining Computations, Literature Data, and PU Learning
Among emerging energy materials, halide and chalcogenide perovskites have garnered significant attention over the last decade owing to the abundance of their constituent species, low manufacturing costs, and their highly tunable composition-structure-property space. Navigating the vast perovskite compositional landscape is possible using density functional theory (DFT) computations, but they are not easily extended to predictions of the synthesizability of new materials and their properties. As…

A Warm-basis Method for Bridging Learning and Iteration: a Case Study in Fluorescence Molecular Tomography
Ruchi Guo, Jiahua Jiang, Bangti Jin, Wuwei Ren, Jianru Zhang
https://arxiv.org/abs/2510.05926 …

A Warm-basis Method for Bridging Learning and Iteration: a Case Study in Fluorescence Molecular Tomography
Fluorescence Molecular Tomography (FMT) is a widely used non-invasive optical imaging technology in biomedical research. It usually faces significant accuracy challenges in depth reconstruction, and conventional iterative methods struggle with poor $z$-resolution even with advanced regularization. Supervised learning approaches can improve recovery accuracy but rely on large, high-quality paired training dataset that is often impractical to acquire in practice. This naturally raises the questio…

Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Games
Brian Hu Zhang, Ioannis Anagnostides, Tuomas Sandholm
https://arxiv.org/abs/2510.04407

Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Games
A considerable chasm has been looming for decades between theory and practice in zero-sum game solving through first-order methods. Although a convergence rate of $T^{-1}$ has long been established since Nemirovski's mirror-prox algorithm and Nesterov's excessive gap technique in the early 2000s, the most effective paradigm in practice is *counterfactual regret minimization*, which is based on *regret matching* and its modern variants. In particular, the state of the art across most benchmarks …

Bridging Collaborative Filtering and Large Language Models with Dynamic Alignment, Multimodal Fusion and Evidence-grounded Explanations
Bo Ma, LuYao Liu, Simon Lau, Chandler Yuan, and XueY Cui, Rosie Zhang
https://arxiv.org/abs/2510.01606

Bridging Collaborative Filtering and Large Language Models with Dynamic Alignment, Multimodal Fusion and Evidence-grounded Explanations
Recent research has explored using Large Language Models for recommendation tasks by transforming user interaction histories and item metadata into text prompts, then having the LLM produce rankings or recommendations. A promising approach involves connecting collaborative filtering knowledge to LLM representations through compact adapter networks, which avoids expensive fine-tuning while preserving the strengths of both components. Yet several challenges persist in practice: collaborative filt…

Bridging Clinical Narratives and ACR Appropriateness Guidelines: A Multi-Agent RAG System for Medical Imaging Decisions
Satrio Pambudi, Filippo Menolascina
https://arxiv.org/abs/2510.04969

Bridging Clinical Narratives and ACR Appropriateness Guidelines: A Multi-Agent RAG System for Medical Imaging Decisions
The selection of appropriate medical imaging procedures is a critical and complex clinical decision, guided by extensive evidence-based standards such as the ACR Appropriateness Criteria (ACR-AC). However, the underutilization of these guidelines, stemming from the difficulty of mapping unstructured patient narratives to structured criteria, contributes to suboptimal patient outcomes and increased healthcare costs. To bridge this gap, we introduce a multi-agent cognitive architecture that autom…

Oh fun find, there was actually something called Oxide in the history of #Rust already - a formalization attempt:
https://arxiv.org/abs/1903.00982 🦀
cc @…

Oxide: The Essence of Rust
Rust claims to advance industrial programming by bridging the gap between low-level systems programming and high-level application programming. At the heart of the argument that this enables programmers to build more reliable and efficient software is the borrow checker - a novel approach to ownership that aims to balance type system expressivity with usability. And yet, to date there is no core type system that captures Rust's notion of ownership and borrowing, and hence no foundation for rese…

Low-Temperature Skyrmions and Spiral Reorientation Processes in Chiral Magnets with Cubic Anisotropy: Guidelines for Bridging Theory and Experiment
A. O. Leonov, G. G\"odecke, J. Grefe, S. S\"ullow, D. Menzel
https://arxiv.org/abs/2510.07640

Low-Temperature Skyrmions and Spiral Reorientation Processes in Chiral Magnets with Cubic Anisotropy: Guidelines for Bridging Theory and Experiment
We revisit the phenomenological Dzyaloshinskii framework, a central theoretical approach for describing magnetization processes in bulk chiral magnets, and demonstrate how magnetocrystalline cubic anisotropy reshapes the phase diagrams of states and provides the key mechanism stabilizing low-temperature skyrmion phases. We show that, for magnetic field directions along the easy anisotropy axes, the phase diagrams feature stable skyrmion pockets for both signs of the anisotropy constant. We furt…

Video-STAR: Reinforcing Open-Vocabulary Action Recognition with Tools
Zhenlong Yuan, Xiangyan Qu, Chengxuan Qian, Rui Chen, Jing Tang, Lei Sun, Xiangxiang Chu, Dapeng Zhang, Yiwei Wang, Yujun Cai, Shuo Li
https://arxiv.org/abs/2510.08480

Video-STAR: Reinforcing Open-Vocabulary Action Recognition with Tools
Multimodal large language models (MLLMs) have demonstrated remarkable potential in bridging visual and textual reasoning, yet their reliance on text-centric priors often limits their ability to disentangle semantically similar actions in open-vocabulary scenarios. To address this, we propose Video-STAR, a framework that harmonizes contextual sub-motion decomposition with tool-augmented reinforcement learning for open-vocabulary action recognition (OVAR). Unlike prior methods that treat actions …

Climate action is finally moving from promises to practice. The Global Implementation Accelerator is bridging the gap between national climate plans and real-world results.
Here's what's working: Private capital restoring Brazilian forests. Unilever switching to renewables. H&M and IKEA modernizing Vietnam's grid. Companies in Taiwan pooling demand for clean energy.
The breakthrough? Aligning business needs with national climate goals creates wins on both sides.

From Plans to Progress: A Blueprint for Delivering 1.5°C Through the ‘Global Mutirão’
The Global Mutirão sent a clear message: delivering 1.5°C is only possible through shared effort.

AssertGen: Enhancement of LLM-aided Assertion Generation through Cross-Layer Signal Bridging
Hongqin Lyu, Yonghao Wang, Yunlin Du, Mingyu Shi, Zhiteng Chao, Wenxing Li, Tiancheng Wang, Huawei Li
https://arxiv.org/abs/2509.23674

AssertGen: Enhancement of LLM-aided Assertion Generation through Cross-Layer Signal Bridging
Assertion-based verification (ABV) serves as a crucial technique for ensuring that register-transfer level (RTL) designs adhere to their specifications. While Large Language Model (LLM) aided assertion generation approaches have recently achieved remarkable progress, existing methods are still unable to effectively identify the relationship between design specifications and RTL designs, which leads to the insufficiency of the generated assertions. To address this issue, we propose AssertGen, an…

Was machen wir denn eigentlich mit BlueSky?
Würdigen wir, dass die überwiegende Userschaft gewisse Neuankömmlinge in einer #Blockorgie gekickt hat?
Empören wir uns, dass sich im zentralistischen Netzwerk zweifelhafte Charaktere tummeln, und beenden das Bridging vom #Fediverse? (BTW,…

Bluesky hits 40 million users, introduces 'dislikes' beta | TechCrunch
Bluesky is looking to a new signal — "dislikes" — to personalize users' feeds.

Bridging the Gap Between Methodological Research and Statistical Practice: Toward "Translational Simulation Research
Anne-Laure Boulesteix, Patrick Callahan, Luzia Hanssum, Vincent Gaertner, Eva Hoster
https://arxiv.org/abs/2510.05800

Bridging the Gap Between Methodological Research and Statistical Practice: Toward "Translational Simulation Research
Simulations are valuable tools for empirically evaluating the properties of statistical methods and are primarily employed in methodological research to draw general conclusions about methods. In addition, they can often be useful to applied statisticians, who may rely on published simulation results to select an appropriate statistical method for their application. However, on the one hand, applying published simulation results directly to practical settings is frequently challenging, as the s…

Bridging the gap between ultrafast optics and resonant photonics via omni-resonance
Abbas Shiri, Kenneth L. Schepler, Ayman F. Abouraddy
https://arxiv.org/abs/2510.12002 https:/…

Bridging the gap between ultrafast optics and resonant photonics via omni-resonance
High-finesse planar Fabry-P{é}rot (FP) cavities spectrally filter the incident field at discrete resonances, and thus cannot be utilized to resonantly enhance the field of ultrashort pulses. Introducing judicious angular dispersion into a pulse can give rise to `omni-resonance', whereby the entire bandwidth of a spatiotemporally structured ultrafast pulse couples to a single longitudinal cavity resonance, even when the pulse bandwidth far exceeds the resonant linewidth. Here we show that omni-…

WiNPA: Wireless Neural Processing Architecture
Sai Xu, Yanan Du
https://arxiv.org/abs/2510.11150 https://arxiv.org/pdf/2510.11150

WiNPA: Wireless Neural Processing Architecture
This article presents a wireless neural processing architecture (WiNPA), providing a novel perspective for accelerating edge inference of deep neural network (DNN) workloads via joint optimization of wireless and computing resources. WiNPA enables fine-grained integration of wireless communication and edge computing, bridging the research gap between wireless and edge intelligence and significantly improving DNN inference performance. To fully realize its potential, we explore a set of fundamen…

Crosslisted article(s) found for cs.LO. https://arxiv.org/list/cs.LO/new
[1/1]:
- Bridging LLM Planning Agents and Formal Methods: A Case Study in Plan Verification
Keshav Ramani, Vali Tawosi, Salwa Alamir, Daniel Borrajo

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Arthur G. Rattew, Po-Wei Huang, Naixu Guo, Lirand\"e Pira, Patrick Rebentrost
https://arxiv.org/abs/2510.07195

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration into modern deep learning pipelines remains unclear. In this work, we take a step towards bridging this gap by presenting the first fully-coherent quantum implementation of a multilayer neural network with non-linear activation functions. Our constructions mirror widely used deep learning architectures based on ResNet, and consist of residual blocks with m…

Bridging the Physics-Data Gap with FNO-Guided Conditional Flow Matching: Designing Inductive Bias through Hierarchical Physical Constraints
Tsuyoshi Okita
https://arxiv.org/abs/2510.08295

Bridging the Physics-Data Gap with FNO-Guided Conditional Flow Matching: Designing Inductive Bias through Hierarchical Physical Constraints
Conventional time-series generation often ignores domain-specific physical constraints, limiting statistical and physical consistency. We propose a hierarchical framework that embeds the inherent hierarchy of physical laws-conservation, dynamics, boundary, and empirical relations-directly into deep generative models, introducing a new paradigm of physics-informed inductive bias. Our method combines Fourier Neural Operators (FNOs) for learning physical operators with Conditional Flow Matching (C…

PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Zixing Lei, Zibo Zhou, Sheng Yin, Yueru Chen, Qingyao Xu, Weixin Li, Yunhong Wang, Bowei Tang, Wei Jing, Siheng Chen
https://arxiv.org/abs/2510.01708

PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Humanoid whole-body control (WBC) policies trained in simulation often suffer from the sim-to-real gap, which fundamentally arises from simulator inductive bias, the inherent assumptions and limitations of any single simulator. These biases lead to nontrivial discrepancies both across simulators and between simulation and the real world. To mitigate the effect of simulator inductive bias, the key idea is to train policies jointly across multiple simulators, encouraging the learned controller to…

Crosslisted article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/2]:
- Bridging Collaborative Filtering and Large Language Models with Dynamic Alignment, Multimodal Fus...
Bo Ma, LuYao Liu, Simon Lau, Chandler Yuan, and XueY Cui, Rosie Zhang

Bridging Developer Instructions and Code Completion Through Instruction-Aware Fill-in-the-Middle Paradigm
Zhensu Sun, Chengran Yang, Chao Peng, Pengfei Gao, Xiaoning Du, Li Li, David Lo
https://arxiv.org/abs/2509.24637

Bridging Developer Instructions and Code Completion Through Instruction-Aware Fill-in-the-Middle Paradigm
Large Language Models (LLMs) have significantly advanced code completion, yet they often fail when the developer's intent is underspecified in the code context. To address this, developers usually add natural language instructions (e.g., comments) into the code context to clarify their intent. However, existing code LLMs applied for code completion systems merely undergo a fill-in-the-middle (FIM) pre-training, which struggles to leverage this information effectively due to the lack of instruct…

IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
Ningyuan Yang, Guanliang Lyu, Mingchen Ma, Yiyi Lu, Yiming Li, Zhihui Gao, Hancheng Ye, Jianyi Zhang, Tingjun Chen, Yiran Chen
https://arxiv.org/abs/2510.01260

IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
The integration of Large Language Models (LLMs) with Internet-of-Things (IoT) systems faces significant challenges in hardware heterogeneity and control complexity. The Model Context Protocol (MCP) emerges as a critical enabler, providing standardized communication between LLMs and physical devices. We propose IoT-MCP, a novel framework that implements MCP through edge-deployed servers to bridge LLMs and IoT ecosystems. To support rigorous evaluation, we introduce IoT-MCP Bench, the first bench…

Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
Changde Du, Yizhuo Lu, Zhongyu Huang, Yi Sun, Zisen Zhou, Shaozheng Qin, Huiguang He
https://arxiv.org/abs/2509.24298

Bridging the behavior-neural gap: A multimodal AI reveals the brain's geometry of emotion more accurately than human self-reports
The ability to represent emotion plays a significant role in human cognition and social interaction, yet the high-dimensional geometry of this affective space and its neural underpinnings remain debated. A key challenge, the `behavior-neural gap,' is the limited ability of human self-reports to predict brain activity. Here we test the hypothesis that this gap arises from the constraints of traditional rating scales and that large-scale similarity judgments can more faithfully capture the brain'…

QCell: Comprehensive Quantum-Mechanical Dataset Spanning Diverse Biomolecular Fragments
Adil Kabylda, Sergio Su\'arez-Dou, Nils Davoine, Florian N. Br\"unig, Alexandre Tkatchenko
https://arxiv.org/abs/2510.09939

QCell: Comprehensive Quantum-Mechanical Dataset Spanning Diverse Biomolecular Fragments
Recent advances in machine learning force fields (MLFFs) are revolutionizing molecular simulations by bridging the gap between quantum-mechanical (QM) accuracy and the computational efficiency of mechanistic potentials. However, the development of reliable MLFFs for biomolecular systems remains constrained by the scarcity of high-quality, chemically diverse QM datasets that span all of the major classes of biomolecules expressed in living cells. Crucially, such a comprehensive dataset must be c…

Bridging integrated information theory and the free-energy principle in living neuronal networks
Teruki Mayama, Sota Shimizu, Yuki Takano, Dai Akita, Hirokazu Takahashi
https://arxiv.org/abs/2510.04084

Bridging integrated information theory and the free-energy principle in living neuronal networks
The relationship between Integrated Information Theory (IIT) and the Free-Energy Principle (FEP) remains unresolved, particularly with respect to how integrated information, proposed as the intrinsic substrate of consciousness, behaves within variational Bayesian inference. We investigated this issue using dissociated neuronal cultures, previously shown to perform perceptual inference consistent with the FEP. Repeated stimulation from hidden sources induced robust source selectivity: variationa…

Bridging Language Gaps: Advances in Cross-Lingual Information Retrieval with Multilingual LLMs
Roksana Goworek, Olivia Macmillan-Scott, Eda B. \"Ozyi\u{g}it
https://arxiv.org/abs/2510.00908

Bridging Language Gaps: Advances in Cross-Lingual Information Retrieval with Multilingual LLMs
Cross-lingual information retrieval (CLIR) addresses the challenge of retrieving relevant documents written in languages different from that of the original query. Research in this area has typically framed the task as monolingual retrieval augmented by translation, treating retrieval methods and cross-lingual capabilities in isolation. Both monolingual and cross-lingual retrieval usually follow a pipeline of query expansion, ranking, re-ranking and, increasingly, question answering. Recent adv…

Bridged Clustering for Representation Learning: Semi-Supervised Sparse Bridging
Patrick Peixuan Ye, Chen Shani, Ellen Vitercik
https://arxiv.org/abs/2510.07182 https://

Bridged Clustering for Representation Learning: Semi-Supervised Sparse Bridging
We introduce Bridged Clustering, a semi-supervised framework to learn predictors from any unpaired input $X$ and output $Y$ dataset. Our method first clusters $X$ and $Y$ independently, then learns a sparse, interpretable bridge between clusters using only a few paired examples. At inference, a new input $x$ is assigned to its nearest input cluster, and the centroid of the linked output cluster is returned as the prediction $\hat{y}$. Unlike traditional SSL, Bridged Clustering explicitly levera…

Replaced article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new
[1/1]:
- Bridging Quasi-Experimental and Structural Approaches for Robust Evaluation of US Airline Mergers
Gaurab Aryal, Anirban Chattopadhyaya, Federico Ciliberto

Bridging Text and Video Generation: A Survey
Nilay Kumar, Priyansh Bhandari, G. Maragatham
https://arxiv.org/abs/2510.04999 https://arxiv.org/pdf/2510.0499…

Bridging Text and Video Generation: A Survey
Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating coherent visual content from natural language prompts. From its inception, the field has advanced from adversarial models to diffusion-based models, yielding higher-fidelity, temporally consistent outputs. Yet challenges persist, such as alignment, long-range co…

Quantum simulation of nuclear shell model: bridging theory and hardware limitations
Chandan Sarma, Paul Stevenson
https://arxiv.org/abs/2510.02124 https://…

Quantum simulation of nuclear shell model: bridging theory and hardware limitations
In this work, we introduce a new qubit mapping strategy for the Variational Quantum Eigensolver (VQE) applied to nuclear shell model calculations, where each Slater determinant (SD) is mapped to a qubit, rather than assigning qubits to individual single-particle states. While this approach may increase the total number of qubits required in some cases, it enables the construction of simpler quantum circuits that are more compatible with current noisy intermediate-scale quantum (NISQ) devices. W…

Replaced article(s) found for cs.CY. https://arxiv.org/list/cs.CY/new
[2/2]:
- Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
Karim Khamaisi, Oliver Kamer, Bruno Rodrigues, Jan von der Assen, Burkhard Stiller

Bridging the Gap Between Simulated and Real Network Data Using Transfer Learning
Carlos G\"uemes-Palau, Miquel Ferriol-Galm\'es, Jordi Paillisse-Vilanova, Albert L\'opez-Bresc\'o, Pere Barlet-Ros, Albert Cabellos-Aparicio
https://arxiv.org/abs/2510.00956

Bridging the Gap Between Simulated and Real Network Data Using Transfer Learning
Machine Learning (ML)-based network models provide fast and accurate predictions for complex network behaviors but require substantial training data. Collecting such data from real networks is often costly and limited, especially for critical scenarios like failures. As a result, researchers commonly rely on simulated data, which reduces accuracy when models are deployed in real environments. We propose a hybrid approach leveraging transfer learning to combine simulated and real-world data. Usi…

Toward a Robust Biomimetic Hybrid Battery: Bridging Biology, Electrochemistry and Data-Driven Control
Raheel Ali, Rayid Ali
https://arxiv.org/abs/2509.23837 https://

Toward a Robust Biomimetic Hybrid Battery: Bridging Biology, Electrochemistry and Data-Driven Control
Electric vehicles and renewable energy systems need batteries that charge quickly, last many years and still store a lot of energy, but current chemistries struggle to deliver all three. Inspired by electric fish that deliver bursts of current and birds that sleep with half their brains, we propose a hybrid battery concept called SwiftPulse. It combines sodium-ion cells that provide energy with niobium-oxide cells that accept high-power pulses. A pulse-based charger and a battery-management str…

Robust Kirkwood-Buff inversion in complex mixtures via reciprocal-space methods
R\'emi Busselez
https://arxiv.org/abs/2510.04636 https://arxiv.org/pdf/…

Robust Kirkwood-Buff inversion in complex mixtures via reciprocal-space methods
Understanding the relationship between microscopic structure and macroscopic thermodynamic properties is a central challenge in the study of complex fluids. The Kirkwood-Buff (KB) theory offers an elegant and powerful framework for bridging this gap by relating integrals over pair correlation functions to measurable thermodynamic quantities. In multicomponent systems, KB integrals connect directly to derivatives of thermodynamic potentials, including chemical potentials derivatives, partial mol…

Threats to the sustainability of Community Notes on X
Zahra Arjmandi-Lari, Alexios Mantzarlis, Tom Stafford
https://arxiv.org/abs/2510.00650 https://arxiv.…

Threats to the sustainability of Community Notes on X
Community Notes are emerging as an important option for content moderation. The Community Notes system pioneered by Twitter, now known as X, uses a bridging algorithm to identify user-generated context with upvotes across political divides, supposedly spinning consensual gold from partisan straw. It is important to understand the nature of the community behind Community Notes, especially as the feature has now been imitated by several billion-user platforms. We look for signs of stability and d…

PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
Haozhuo Zhang, Michele Caprio, Jing Shao, Qiang Zhang, Jian Tang, Shanghang Zhang, Wei Pan
https://arxiv.org/abs/2509.24591

PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework. At its core, PoseDiff maps raw visual observations into structured robot states-such as 3D keypoints or joint angles-from a single RGB image, eliminating the need for multi-stage pipelines or auxiliary modalities. Building upon this foundation, PoseDiff extends naturally to video-to-action inverse dynamics: by conditioning on sparse video keyframes generated by world mod…

Bridging the Trust Gap in Crowdfunding: A Novel Expert-Based Evaluation Mechanism
Issam Hosni, Omar Talbi
https://arxiv.org/abs/2509.23378 https://arxiv.or…

Bridging the Trust Gap in Crowdfunding: A Novel Expert-Based Evaluation Mechanism
Crowdfunding has emerged as a vital alternative funding source, transforming how creative projects and startups secure financing by directly connecting creators to backers. However, persistent trust issues and information asymmetry between creators and backers significantly hinder its growth and development. Existing trust-enhancement mechanisms, such as third-party endorsements and basic expert validation often lack objectivity and robustness, leaving backers vulnerable to biased signals and p…

Higher-Order Feature Attribution: Bridging Statistics, Explainable AI, and Topological Signal Processing
Kurt Butler, Guanchao Feng, Petar Djuric
https://arxiv.org/abs/2510.06165

Higher-Order Feature Attribution: Bridging Statistics, Explainable AI, and Topological Signal Processing
Feature attributions are post-training analysis methods that assess how various input features of a machine learning model contribute to an output prediction. Their interpretation is straightforward when features act independently, but becomes less direct when the predictive model involves interactions such as multiplicative relationships or joint feature contributions. In this work, we propose a general theory of higher-order feature attribution, which we develop on the foundation of Integrate…

Replaced article(s) found for cs.OS. https://arxiv.org/list/cs.OS/new
[1/1]:
- Demystifying Serverless Costs on Public Platforms: Bridging Billing, Architecture, and OS Scheduling
Changyuan Lin, Yuanzhi Ma, Mohammad Shahrad

Items Proxy Bridging: Enabling Frictionless Critiquing in Knowledge Graph Recommendations
Huanyu Zhang, Xiaoxuan Shen, Yu Lei, Baolin Yi, Jianfang Liu, Yinao xie
https://arxiv.org/abs/2509.26107

Items Proxy Bridging: Enabling Frictionless Critiquing in Knowledge Graph Recommendations
Modern recommender systems place great inclination towards facilitating user experience, as more applications enabling users to critique and then refine recommendations immediately. Considering the real-time requirements, critique-able recommender systems typically straight modify the model parameters and update the recommend list through analyzing the user critiquing keyphrases in the inference phase. Current critiquing methods require first constructing a specially designated model which esta…

Unifying local and nonlocal corrosion frameworks: A convergent nonlocal extension of the KKS phase-field model
Christian J. Cyron, Marvin Fritz, Alexander Hermann, Tobias K\"oppl, Arman Shojaei, Stewart Silling
https://arxiv.org/abs/2509.23503

Unifying local and nonlocal corrosion frameworks: A convergent nonlocal extension of the KKS phase-field model
We introduce a nonlocal extension of the Kim-Kim-Suzuki (KKS) phase-field corrosion model aimed at bridging local and nonlocal corrosion modeling approaches, such as phase-field and peridynamic frameworks. In this formulation, classical gradient operators are replaced with integral operators defined over a finite interaction horizon, naturally embedding an intrinsic length scale that aligns with nonlocal theories like peridynamics. Under precise assumptions on function spaces and kernel functio…

CHRONOS: Cryogenic sub-Hz cROss torsion bar detector with quantum NOn-demolition Speed meter
Yuki Inoue, Hsiang-Chieh Hsu, Hsiang-Yu Huang, M. Afif Ismail, Vivek Kumar, Miftahul Ma'arif, Avani Patel, Daiki Tanabe, Henry Tsz-King Wong, Da-Chun Yu
https://arxiv.org/abs/2509.23172

CHRONOS: Cryogenic sub-Hz cROss torsion bar detector with quantum NOn-demolition Speed meter
We propose a next-generation ground-based gravitational-wave detector, the Cryogenic sub-Hz cROss torsion-bar detector with quantum NOn-demolition Speed meter (CHRONOS), optimized for the unexplored 0.1-10Hz band bridging the gap between the space-based LISA and future ground-based detectors such as Cosmic Explorer and the Einstein Telescope. CHRONOS combines a ring-cavity Sagnac interferometer with torsion-bar test masses to realize the first quantum nondemolition (QND) measurement of angular …

Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials
Jaesun Kim, Jinmu You, Yutack Park, Yunsung Lim, Yujin Kang, Jisu Kim, Haekwan Jeon, Deokgi Hong, Seung Yul Lee, Saerom Choi, Yongdeok Kim, Jae W. Lee, Seungwu Han
https://arxiv.org/abs/2510.11241

Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials
Accurate yet transferable machine-learning interatomic potentials (MLIPs) are essential for accelerating materials and chemical discovery. However, most universal MLIPs overfit to narrow datasets or computational protocols, limiting their reliability across chemical and functional domains. We introduce a transferable multi-domain training strategy that jointly optimizes universal and task-specific parameters through selective regularization, coupled with a domain-bridging set (DBS) that aligns …

Crosslisted article(s) found for cs.SC. https://arxiv.org/list/cs.SC/new
[1/1]:
- AI Noether -- Bridging the Gap Between Scientific Laws Derived by AI Systems and Canonical Knowle...
Karan Srivastava, Sanjeeb Dash, Ryan Cory-Wright, Barry Trager, Lior Horesh

A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System
Jiale Guo, Suizhi Huang, Mei Li, Dong Huang, Xingsheng Chen, Regina Zhang, Zhijiang Guo, Han Yu, Siu-Ming Yiu, Christian Jensen, Pietro Lio, Kwok-Yan Lam
https://arxiv.org/abs/2510.09721

A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System
The integration of LLMs into software engineering has catalyzed a paradigm shift from traditional rule-based systems to sophisticated agentic systems capable of autonomous problem-solving. Despite this transformation, the field lacks a comprehensive understanding of how benchmarks and solutions interconnect, hindering systematic progress and evaluation. This survey presents the first holistic analysis of LLM-empowered software engineering, bridging the critical gap between evaluation and soluti…

Neural Tangent Kernels for Complex Genetic Risk Prediction: Bridging Deep Learning and Kernel Methods in Genomics
Heng Ge, Qing Lu
https://arxiv.org/abs/2510.01426 https://

Neural Tangent Kernels for Complex Genetic Risk Prediction: Bridging Deep Learning and Kernel Methods in Genomics
Given the complexity of genetic risk prediction, there is a critical need for the development of novel methodologies that can effectively capture intricate genotype--phenotype relationships (e.g., nonlinear) while remaining statistically interpretable and computationally tractable. We develop a Neural Tangent Kernel (NTK) framework to integrate kernel methods into deep neural networks for genetic risk prediction analysis. We consider two approaches: NTK-LMM, which embeds the empirical NTK in a …

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Bridging Memory Gaps: Scaling Federated Learning for Heterogeneous Clients
Yebo Wu, Jingguang Li, Chunlin Tian, Kahou Tam, Li Li, Chengzhong Xu

Bridging Language Models and Formal Methods for Intent-Driven Optical Network Design
Anis Bekri, Amar Abane, Abdella Battou, Saddek Bensalem
https://arxiv.org/abs/2509.22834 htt…

Bridging Language Models and Formal Methods for Intent-Driven Optical Network Design
Intent-Based Networking (IBN) aims to simplify network management by enabling users to specify high-level goals that drive automated network design and configuration. However, translating informal natural-language intents into formally correct optical network topologies remains challenging due to inherent ambiguity and lack of rigor in Large Language Models (LLMs). To address this, we propose a novel hybrid pipeline that integrates LLM-based intent parsing, formal methods, and Optical Retrieval…

Replaced article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Demystifying Serverless Costs on Public Platforms: Bridging Billing, Architecture, and OS Scheduling
Changyuan Lin, Yuanzhi Ma, Mohammad Shahrad

Translating Milli/Microrobots with A Value-Centered Readiness Framework
Hakan Ceylan, Edoardo Sinibaldi, Sanjay Misra, Pankaj J. Pasricha, Dietmar W. Hutmacher
https://arxiv.org/abs/2510.12090

Translating Milli/Microrobots with A Value-Centered Readiness Framework
Untethered mobile milli/microrobots hold transformative potential for interventional medicine by enabling more precise and entirely non-invasive diagnosis and therapy. Realizing this promise requires bridging the gap between groundbreaking laboratory demonstrations and successful clinical integration. Despite remarkable technical progress over the past two decades, most millirobots and microrobots remain confined to laboratory proof-of-concept demonstrations, with limited real-world feasibility…

Bridging Mid-IR and Terahertz Domains in a Single High-Resolution Dual-Comb Spectroscopy Measurement
D. Konnov, A. Muraviev, K. L. Vodopyanov
https://arxiv.org/abs/2509.25468 ht…

Bridging Mid-IR and Terahertz Domains in a Single High-Resolution Dual-Comb Spectroscopy Measurement
Dual-comb spectroscopy (DCS) utilizes a pair of broadband mutually coherent laser frequency combs to enable high-resolution, high-accuracy spectroscopic measurements with atomic-clock-level frequency referencing, and rapid, multiplexed acquisition without moving parts. It has traditionally been confined to specific domains: terahertz, infrared, visible, and ultraviolet, each requiring distinct comb sources and detection mechanisms tailored to the nature of the spectroscopic target. Yet, similar…

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Hyemi Song, Matthew Johnson, Kirsten Whitley, Eric Krokos, Amitabh Varshney
https://arxiv.org/abs/2510.12156

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Interaction (NLI) for visual analytics in immersive environments, users' speech patterns and their use of embodiment cues in speech remain underexplored. Understanding their interplay is crucial to bridging the gap between users' intent and an immersive analytic system. To address this, we report the results from 15 partici…

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Mohammad Tamim Kashifi
https://arxiv.org/abs/2510.09886

Modelling Intra-driver Behavioral Adaptation through Risk Sensitivity and Regime Transitions: A Task-difficulty Car-following Model
Over the past decade, there has been a growing trend toward integrating human factors (HF) into traffic flow models to better understand the complexities of human behavior and its impact on traffic dynamics. This research seeks to advance this trend by bridging the gap between traditional car-following models and the inherent variability of human driving behavior. By incorporating these elements, our models provide valuable insights into how driver behavior adaptation and risk-taking influence …

Transferable Generative Models Bridge Femtosecond to Nanosecond Time-Step Molecular Dynamics
Juan Viguera Diez, Mathias Schreiner, Simon Olsson
https://arxiv.org/abs/2510.07589 …

Transferable Generative Models Bridge Femtosecond to Nanosecond Time-Step Molecular Dynamics
Understanding molecular structure, dynamics, and reactivity requires bridging processes that occur across widely separated time scales. Conventional molecular dynamics simulations provide atomistic resolution, but their femtosecond time steps limit access to the slow conformational changes and relaxation processes that govern chemical function. Here, we introduce a deep generative modeling framework that accelerates sampling of molecular dynamics by four orders of magnitude while retaining phys…

Sketch Animation: State-of-the-art Report
Gaurav Rai, Ojaswa Sharma
https://arxiv.org/abs/2510.10218 https://arxiv.org/pdf/2510.10218

Sketch Animation: State-of-the-art Report
Sketch animation has emerged as a transformative technology, bridging art and science to create dynamic visual narratives across various fields such as entertainment, education, healthcare, and virtual reality. This survey explores recent trends and innovations in sketch animation, with a focus on methods that have advanced the state of the art. The paper categorizes and evaluates key methodologies, including keyframe interpolation, physics-based animation, data-driven, motion capture, and deep…

Bridging Caribbean Literature and Digital Humanities
https://ift.tt/MZcaCHU
updated: Wednesday, October 1, 2025 - 1:52pmfull name / name of organization: Special issue editors:…
via Input 4 RELCFP

Spatially-informed transformers: Injecting geostatistical covariance biases into self-attention for spatio-temporal forecasting
Yuri Calleo
https://arxiv.org/abs/2512.17696 https://arxiv.org/pdf/2512.17696 https://arxiv.org/html/2512.17696
arXiv:2512.17696v1 Announce Type: new
Abstract: The modeling of high-dimensional spatio-temporal processes presents a fundamental dichotomy between the probabilistic rigor of classical geostatistics and the flexible, high-capacity representations of deep learning. While Gaussian processes offer theoretical consistency and exact uncertainty quantification, their prohibitive computational scaling renders them impractical for massive sensor networks. Conversely, modern transformer architectures excel at sequence modeling but inherently lack a geometric inductive bias, treating spatial sensors as permutation-invariant tokens without a native understanding of distance. In this work, we propose a spatially-informed transformer, a hybrid architecture that injects a geostatistical inductive bias directly into the self-attention mechanism via a learnable covariance kernel. By formally decomposing the attention structure into a stationary physical prior and a non-stationary data-driven residual, we impose a soft topological constraint that favors spatially proximal interactions while retaining the capacity to model complex dynamics. We demonstrate the phenomenon of ``Deep Variography'', where the network successfully recovers the true spatial decay parameters of the underlying process end-to-end via backpropagation. Extensive experiments on synthetic Gaussian random fields and real-world traffic benchmarks confirm that our method outperforms state-of-the-art graph neural networks. Furthermore, rigorous statistical validation confirms that the proposed method delivers not only superior predictive accuracy but also well-calibrated probabilistic forecasts, effectively bridging the gap between physics-aware modeling and data-driven learning.
toXiv_bot_toot

Allometric scaling of brain activity explained by avalanche criticality
Tiago S. A. N. Sim\~oes, Jos\'e S. Andrade Jr., Hans J. Herrmann, Stefano Zapperi, Lucilla de Arcangelis
https://arxiv.org/abs/2512.10834 https://arxiv.org/pdf/2512.10834 https://arxiv.org/html/2512.10834
arXiv:2512.10834v1 Announce Type: new
Abstract: Allometric scaling laws, such as Kleiber's law for metabolic rate, highlight how efficiency emerges with size across living systems. The brain, with its characteristic sublinear scaling of activity, has long posed a puzzle: why do larger brains operate with disproportionately lower firing rates? Here we show that this economy of scale is a universal outcome of avalanche dynamics. We derive analytical scaling laws directly from avalanche statistics, establishing that any system governed by critical avalanches must exhibit sublinear activity-size relations. This theoretical prediction is then verified in integrate-and-fire neuronal networks at criticality and in classical self-organized criticality models, demonstrating that the effect is not model-specific but generic. The predicted exponents align with experimental observations across mammal species, bridging dynamical criticality with the allometry of brain metabolism. Our results reveal avalanche criticality as a fundamental mechanism underlying Kleiber-like scaling in the brain.
toXiv_bot_toot

A quantum-coherent photon--emitter interface in the original telecom band
Marcus Albrechtsen, Severin Kr\"uger, Juan Loredo, Lucio Stefan, Zhe Liu, Yu Meng, Lukas L. Niekamp, Bianca F. Seyschab, Nikolai Spitzer, Richard J. Warburton, Peter Lodahl, Arne Ludwig, Leonardo Midolo
https://arxiv.org/abs/2510.09251

A quantum-coherent photon--emitter interface in the original telecom band
Quantum dots stand out as the most advanced and versatile light-matter interface available today. Their ability to deliver high-quality, high-rate, and pure photons has set benchmarks that far surpass other emitters. Yet, a critical frontier has remained elusive: achieving these exceptional capabilities at telecom wavelengths, bridging the gap to fiber-optic infrastructure and scalable silicon photonics. Overcoming this challenge demands high quality quantum materials and devices which, despite…

Replaced article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new
[1/1]:
- Bridging Quasi-Experimental and Structural Approaches for Robust Evaluation of US Airline Mergers
Gaurab Aryal, Anirban Chattopadhyaya, Federico Ciliberto

Net-Zero 6G from Earth to Orbit: Sustainable Design of Integrated Terrestrial and Non-Terrestrial Networks
Muhammad Ali Jamshed, Malik Muhammad Saad, Muhammad Ahmed Mohsin, Dongkyun Kim, Octavia A. Dobre, Halim Yanikomeroglu, Lina Mohjazi
https://arxiv.org/abs/2510.00678

Net-Zero 6G from Earth to Orbit: Sustainable Design of Integrated Terrestrial and Non-Terrestrial Networks
The integration of Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN) plays a crucial role in bridging the digital divide and enabling Sixth Generation (6G) and beyond to achieve truly ubiquitous connectivity. However, combining TN and NTN introduces significant energy challenges due to the diverse characteristics and operational environments of these systems. In this paper, we present for the first time a comprehensive overview of the design challenges associated with achieving Net-Z…

ActiveUMI: Robotic Manipulation with Active Perception from Robot-Free Human Demonstrations
Qiyuan Zeng, Chengmeng Li, Jude St. John, Zhongyi Zhou, Junjie Wen, Guorui Feng, Yichen Zhu, Yi Xu
https://arxiv.org/abs/2510.01607

ActiveUMI: Robotic Manipulation with Active Perception from Robot-Free Human Demonstrations
We present ActiveUMI, a framework for a data collection system that transfers in-the-wild human demonstrations to robots capable of complex bimanual manipulation. ActiveUMI couples a portable VR teleoperation kit with sensorized controllers that mirror the robot's end-effectors, bridging human-robot kinematics via precise pose alignment. To ensure mobility and data quality, we introduce several key techniques, including immersive 3D model rendering, a self-contained wearable computer, and effic…