Tootfinder

Thermal Transport Anomalies of Electrolyte Solutions in the Water Supercooled Regime: Signatures of the Liquid-Liquid Water Phase Transition
Guansen Zhao, Fernando Bresme
https://arxiv.org/abs/2508.21751

Thermal Transport Anomalies of Electrolyte Solutions in the Water Supercooled Regime: Signatures of the Liquid-Liquid Water Phase Transition
Water exhibits remarkable anomalies when supercooled, attributed to a hypothesized liquid-liquid phase transition (LLPT) between low-density (LDL) and high-density (HDL) liquid phases. Using non-equilibrium molecular dynamics simulations, we explore thermal transport and coupled effects in supercooled NaCl and LiCl solutions (1-4 m, 200-300 K). At 1 m, thermal conductivity exhibits a pronounced minimum near 220 K, coinciding with maxima in isothermal compressibility and minima in the speed of s…

Style4D-Bench: A Benchmark Suite for 4D Stylization
Beiqi Chen, Shuai Shao, Haitang Feng, Jianhuang Lai, Jianlou Si, Guangcong Wang
https://arxiv.org/abs/2508.19243 https://

Style4D-Bench: A Benchmark Suite for 4D Stylization
We introduce Style4D-Bench, the first benchmark suite specifically designed for 4D stylization, with the goal of standardizing evaluation and facilitating progress in this emerging area. Style4D-Bench comprises: 1) a comprehensive evaluation protocol measuring spatial fidelity, temporal coherence, and multi-view consistency through both perceptual and quantitative metrics, 2) a strong baseline that make an initial attempt for 4D stylization, and 3) a curated collection of high-resolution dynami…

Emotion Omni: Enabling Empathetic Speech Response Generation through Large Language Models
Haoyu Wang, Guangyan Zhang, Jiale Chen, Jingyu Li, Yuehai Wang, Yiwen Guo
https://arxiv.org/abs/2508.18655

Emotion Omni: Enabling Empathetic Speech Response Generation through Large Language Models
With the development of speech large language models (speech LLMs), users can now interact directly with assistants via speech. However, most existing models simply convert the response content into speech without fully understanding the rich emotional and paralinguistic cues embedded in the user's query. In many cases, the same sentence can have different meanings depending on the emotional expression. Furthermore, emotional understanding is essential for improving user experience in human-mac…

A Comprehensive Survey of Website Fingerprinting Attacks and Defenses in Tor: Advances and Open Challenges
Yuwen Cui, Guangjing Wang, Khanh Vu, Kai Wei, Kehan Shen, Zhengyuan Jiang, Xiao Han, Ning Wang, Zhuo Lu, Yao Liu
https://arxiv.org/abs/2510.11804

A Comprehensive Survey of Website Fingerprinting Attacks and Defenses in Tor: Advances and Open Challenges
The Tor network provides users with strong anonymity by routing their internet traffic through multiple relays. While Tor encrypts traffic and hides IP addresses, it remains vulnerable to traffic analysis attacks such as the website fingerprinting (WF) attack, achieving increasingly high fingerprinting accuracy even under open-world conditions. In response, researchers have proposed a variety of defenses, ranging from adaptive padding, traffic regularization, and traffic morphing to adversarial…

Idiosyncratic Versus Normative Modeling of Atypical Speech Recognition: Dysarthric Case Studies
Vishnu Raja, Adithya V Ganesan, Anand Syamkumar, Ritwik Banerjee, H Andrew Schwartz
https://arxiv.org/abs/2509.16718

Idiosyncratic Versus Normative Modeling of Atypical Speech Recognition: Dysarthric Case Studies
State-of-the-art automatic speech recognition (ASR) models like Whisper, perform poorly on atypical speech, such as that produced by individuals with dysarthria. Past works for atypical speech have mostly investigated fully personalized (or idiosyncratic) models, but modeling strategies that can both generalize and handle idiosyncracy could be more effective for capturing atypical speech. To investigate this, we compare four strategies: (a) $\textit{normative}$ models trained on typical speech …

The Euler-Maruyama method for SDEs with low-regularity drift
Jinlong Wei, Junhao Hu, Guangying Lv, Chenggui Yuan
https://arxiv.org/abs/2508.10512 https://a…

The Euler-Maruyama method for SDEs with low-regularity drift
We study the strong $L^p$-convergence rates of the Euler-Maruyama method for stochastic differential equations driven by Brownian motion with low-regularity drift coefficients. Specifically, the drift is assumed to be in the Lebesgue-Hölder spaces $L^q([0,T]; {\mathcal C}_b^α({\mathbb R}^d))$ with $α\in(0,1)$ and $q\in (2/(1+α),\infty]$. For every $p\geq 2$, by using stochastic sewing and/or the Itô-Tanaka trick, we obtain the $L^p$-convergence rates: $(1+α)/2$ for $q\in [2,\infty]$ and $…

A Geomechanically-Informed Framework for Wellbore Trajectory Prediction: Integrating First-Principles Kinematics with a Rigorous Derivation of Gated Recurrent Networks
Shubham Kumar, Anshuman Sahoo
https://arxiv.org/abs/2510.07564

A Geomechanically-Informed Framework for Wellbore Trajectory Prediction: Integrating First-Principles Kinematics with a Rigorous Derivation of Gated Recurrent Networks
Accurate wellbore trajectory prediction is a paramount challenge in subsurface engineering, governed by complex interactions between the drilling assembly and heterogeneous geological formations. This research establishes a comprehensive, mathematically rigorous framework for trajectory prediction that moves beyond empirical modeling to a geomechanically-informed, data-driven surrogate approach.The study leverages Log ASCII Standard (LAS) and wellbore deviation (DEV) data from 14 wells in the G…

A Comprehensive All-Sky Catalog of 3345 Molecular Clouds from Three-dimensional Dust Extinction
Tao Wang, Haibo Yuan, Bingqiu Chen, Guangxing Li, Bowen Huang, Helong Guo, Ruoyi Zhang
https://arxiv.org/abs/2509.07670

A Comprehensive All-Sky Catalog of 3345 Molecular Clouds from Three-dimensional Dust Extinction
Understanding the distribution and properties of molecular clouds is crucial for tracing the structure and evolution of the interstellar medium and the large-scale morphology of the Milky Way. Here we present an all-sky catalog of 3,345 molecular clouds identified from our previous three-dimensional dust reddening map using a dendrogram-based clustering method with distance-adaptive parameters. The catalog spans heliocentric distances from 90 pc to 4.3 kpc and includes key physical properties f…

CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
Xiaoji Zheng, Ziyuan Yang, Yanhao Chen, Yuhang Peng, Yuanrong Tang, Gengyuan Liu, Bokui Chen, Jiangtao Gong
https://arxiv.org/abs/2510.12560

CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
End-to-end autonomous driving models trained solely with imitation learning (IL) often suffer from poor generalization. In contrast, reinforcement learning (RL) promotes exploration through reward maximization but faces challenges such as sample inefficiency and unstable convergence. A natural solution is to combine IL and RL. Moving beyond the conventional two-stage paradigm (IL pretraining followed by RL fine-tuning), we propose CoIRL-AD, a competitive dual-policy framework that enables IL an…

A Survey on Non-Intrusive ASR Refinement: From Output-Level Correction to Full-Model Distillation
Mohammad Reza Peyghan, Fatemeh Rajabi, Saman Soleimani Roudi, Saeedreza Zouashkiani, Sajjad Amini, Shahrokh Ghaemmaghami
https://arxiv.org/abs/2508.07285

A Survey on Non-Intrusive ASR Refinement: From Output-Level Correction to Full-Model Distillation
Automatic Speech Recognition (ASR) has become an integral component of modern technology, powering applications such as voice-activated assistants, transcription services, and accessibility tools. Yet ASR systems continue to struggle with the inherent variability of human speech, such as accents, dialects, and speaking styles, as well as environmental interference, including background noise. Moreover, domain-specific conversations often employ specialized terminology, which can exacerbate tran…