Tootfinder

I have never been a mac fan. I've never watched a live mac announcement.
bah. humbug!

Since @… alerted me to Salerno, Italy slow drone-doom project NIGHTSCAPE's new EP last week, I noticed the project also has a self-titled LP from earlier this year. And just like the EP, it's EXCELLENT. DAMN, am I a fan of drone-doom like this. FFO Black Sky Giant, Pelican, etc.
Nightscape (Vol. 1) LP from January:

Watch reactions from the FINAL EPISODE of #StarWars #Andor.
▶️ REACTIONARYtv | Andor 2X12 | "Jedha, Kyber, Erso" | Fan Reactions

ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction
Changsheng Fang, Yongtong Liu, Bahareh Morovati, Shuo Han, Yu Shi, Li Zhou, Shuyi Fan, Hengyong Yu
https://arxiv.org/abs/2506.06400

ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction
Sparse-view computed tomography (CT) is a practical solution to reduce radiation dose, but the resulting ill-posed inverse problem poses significant challenges for accurate image reconstruction. Although deep learning and diffusion-based methods have shown promising results, they often lack physical interpretability or suffer from high computational costs due to iterative sampling starting from random noise. Recent advances in generative modeling, particularly Poisson Flow Generative Models (PF…

One of my favourite peertube channels btw is @… who in this inspiring video, explains how she makes all her vids on linux.
If I ever get more time, I will seriously follow some of these recommendations - I'm already a fan of @…
https://tilvids.com/w/p4pRnBvNGGAAafD5KtDSvs

Position: Simulating Society Requires Simulating Thought
Chance Jiajie Li, Jiayi Wu, Zhenze Mo, Ao Qu, Yuhan Tang, Kaiya Ivy Zhao, Yulu Gan, Jie Fan, Jiangbo Yu, Jinhua Zhao, Paul Liang, Luis Alonso, Kent Larson
https://arxiv.org/abs/2506.06958

Position: Simulating Society Requires Simulating Thought
Simulating society with large language models (LLMs), we argue, requires more than generating plausible behavior -- it demands cognitively grounded reasoning that is structured, revisable, and traceable. LLM-based agents are increasingly used to emulate individual and group behavior -- primarily through prompting and supervised fine-tuning. Yet they often lack internal coherence, causal reasoning, and belief traceability -- making them unreliable for analyzing how people reason, deliberate, or …

Regenerating Daily Routines for Young Adults with Depression through User-Led Indoor Environment Modifications Using Local Natural Materials
Ziqun Hua, Ao Jiang, Haoling Yang, Hao Fan, Huizhong Hu, Bernard Foing
https://arxiv.org/abs/2506.05729

Regenerating Daily Routines for Young Adults with Depression through User-Led Indoor Environment Modifications Using Local Natural Materials
Young adults with depression often experience prolonged indoor stays, limiting their access to natural environments and exacerbating mental health challenges. While nature therapy is recognized for its psychological benefits, existing interventions frequently require outdoor engagement, which may not be accessible for all individuals. This study explores the potential of user-led indoor modifications using local natural materials as a mental health intervention. A qualitative approach wasemploy…

#happypride

Nick Offerman slams 'Parks and Rec' fan insinuating Ron Swanson is homophobic
Nick Offerman is standing up for queer 'Parks and Rec' fans after a user shared a manipulated image of his character, Ron Swanson, to spread homophobic hate: 'You dumb f---.

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization
Zhican Wang, Guanghui He, Dantong Liu, Lingjun Gao, Shell Xu Hu, Chen Zhang, Zhuoran Song, Nicholas Lane, Wayne Luk, Hongxiang Fan
https://arxiv.org/abs/2506.07069

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization
3D Gaussian Splatting (3DGS) has recently gained significant attention for high-quality and efficient view synthesis, making it widely adopted in fields such as AR/VR, robotics, and autonomous driving. Despite its impressive algorithmic performance, real-time rendering on resource-constrained devices remains a major challenge due to tight power and area budgets. This paper presents an architecture-algorithm co-design to address these inefficiencies. First, we reveal substantial redundancy cause…

Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu, Jiahao Fan, Yanan Sun
https://arxiv.org/abs/2506.06019 h…

Runtime Analysis of Evolutionary NAS for Multiclass Classification
Evolutionary neural architecture search (ENAS) is a key part of evolutionary machine learning, which commonly utilizes evolutionary algorithms (EAs) to automatically design high-performing deep neural architectures. During past years, various ENAS methods have been proposed with exceptional performance. However, the theory research of ENAS is still in the infant. In this work, we step for the runtime analysis, which is an essential theory aspect of EAs, of ENAS upon multiclass classification pr…

I am watching #psgars
I don't like football.
I also drink beer.
I am not a huge fan of beer.
But guess what? I love my wife, and she likes both football and beer.
And she loves me, so I'm OK with this boring shit. 😊
#football

NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems
Zuowu Zheng, Ze Wang, Fan Yang, Wenqing Ye, Weihua Huang, Wenqiang He, Teng Zhang, Xingxing Wang
https://arxiv.org/abs/2506.05685

NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems
Online advertising auctions are fundamental to internet commerce, demanding solutions that not only maximize revenue but also ensure incentive compatibility, high-quality user experience, and real-time efficiency. While recent learning-based auction frameworks have improved context modeling by capturing intra-list dependencies among ads, they remain limited in addressing global externalities and often suffer from inefficiencies caused by sequential processing. In this work, we introduce the Non…

#Google #PixelBuds 2
Für den stark rabattierten Kauf eine gute Gelegenheit. Klingen voll und satt und sitzen - obwohl ich kein InEar-Fan bin - gut und angenehm.

Google Pixel Buds 2
Die Frau hat neulich ein Google Pixel 9a bekommen, weil wir einen Gutscheincode von Google hatten und inkl. dem Trade-In vom alten Google Pixel 4a 5G war es ein wohlfeiler Preis. Zudem gab es obendrauf noch die Google Pixel Buds …

Google Pixel Buds 2 Weiterlesen »

I’m a big enough Stereolab fan to know the song I can faintly hear issuing from the bar next door is off _Cobra and Phases Group_, but not to know the song title

Ich bin da ja kein Fan von, aaaaber...
Das ist eines der besten Musikvideos, die ich seit längerem gesehen habe.
Jede Szene eine Überraschung.
https://youtu.be/aSugSGCC12I?si=X8wHZgbZqknC1dX8

ViT-based Local Volume dwarf galaxy Identificationin (VIDA) in the CSST survey
Han Qu, Zhen Yuan, Chengliang Wei, Chao Liu, Jiang Chang, Guoliang Li, Nicolas F. Martin, Chaowei Tsai, Shi Shao, Yu Luo, Ran Li, Xi Kang, Xiangxiang Xue, Zhou Fan
https://arxiv.org/abs/2506.04361

ViT-based Local Volume dwarf galaxy Identificationin (VIDA) in the CSST survey
Identifying dwarf galaxies within the Local Volume is crucial for constraining the luminosity function of satellite galaxies in the nearby universe. We report the detection capabilities of dwarf galaxies within the Local Volume using the Chinese Space Station Telescope (CSST). Based on the simulated imaging data of CSST, we develop a detection and classification pipeline that combines traditional image-based search techniques with advanced machine learning classification models. The simulated L…

Spatiotemporal Prediction of Electric Vehicle Charging Load Based on Large Language Models
Hang Fan, Mingxuan Li, Jingshi Cui, Zuhan Zhang, Wencai Run, Dunnan Liu
https://arxiv.org/abs/2506.03728

Spatiotemporal Prediction of Electric Vehicle Charging Load Based on Large Language Models
The rapid growth of EVs and the subsequent increase in charging demand pose significant challenges for load grid scheduling and the operation of EV charging stations. Effectively harnessing the spatiotemporal correlations among EV charging stations to improve forecasting accuracy is complex. To tackle these challenges, we propose EV-LLM for EV charging loads based on LLMs in this paper. EV-LLM integrates the strengths of Graph Convolutional Networks (GCNs) in spatiotemporal feature extraction w…

A Fan-type condition involving bipartite independence number for hamiltonicity in graphs
Hongxi Liu, Long-Tu Yuan, Xiaowen Zhang
https://arxiv.org/abs/2506.02687

A Fan-type condition involving bipartite independence number for hamiltonicity in graphs
The bipartite independence number of a graph $G$, denoted by $\widetildeα(G)$, is defined as the smallest integer $q$ for which there exist positive integers $s$ and $t$ satisfying $s + t = q + 1$, such that for any two disjoint subsets $A, B \subseteq V(G)$ with $|A| = s$ and $|B| = t$, there exists an edge between $A$ and $B$. In this paper, we prove that for a $2$-connected graph $G$ of order at least three, if $\max\{d_G(x),d_G(y)\}\geq \widetildeα(G)$ for any pair of …

A Scalable Exponential Random Graph Model: Amortised Hierarchical Sequential Neural Posterior Estimation with Applications in Neuroscience
Yefeng Fan, Simon Richard White
https://arxiv.org/abs/2506.04558

A Scalable Exponential Random Graph Model: Amortised Hierarchical Sequential Neural Posterior Estimation with Applications in Neuroscience
Exponential Random Graph Models (ERGMs) are an inferential model for analysing statistical networks. Recent development in ERGMs uses hierarchical Bayesian setup to jointly model a group of networks, which is called a multiple-network Exponential Random Graph Model (MN-ERGMs). MN-ERGM has been successfully applied on real-world resting-state fMRI data from the Cam-CAN project to infer the brain connectivity on aging. However, conventional Bayesian ERGM estimation approach is computationally int…

Note on the interpretation of magnetic diffraction in NdAlSi: helical or fan?
Takashi Kurumaji
https://arxiv.org/abs/2506.04000 https://

Note on the interpretation of magnetic diffraction in NdAlSi: helical or fan?
We revisit the magnetic structure analysis reported in Nat. Mater. 20, 1650 (2021), which concluded that a Weyl semimetal candidate NdAlSi hosts a helical magnetic order. This conclusion was based on magnetic neutron diffraction peaks corresponding to modulation vectors $\vec{k}_{in} = (1/3, 1/3, 0)$ and $\vec{k}_{out} = (2/3, 2/3, 0)$, attributed to in-plane and out-of-plane components of the magnetic moments, respectively. Upon careful reanalysis, we suggest that a fan-type magnetic structure…

MVP-Shapley: Feature-based Modeling for Evaluating the Most Valuable Player in Basketball
Haifeng Sun, Yu Xiong, Runze Wu, Kai Wang, Lan Zhang, Changjie Fan, Shaojie Tang, Xiang-Yang Li
https://arxiv.org/abs/2506.04602

MVP-Shapley: Feature-based Modeling for Evaluating the Most Valuable Player in Basketball
The burgeoning growth of the esports and multiplayer online gaming community has highlighted the critical importance of evaluating the Most Valuable Player (MVP). The establishment of an explainable and practical MVP evaluation method is very challenging. In our study, we specifically focus on play-by-play data, which records related events during the game, such as assists and points. We aim to address the challenges by introducing a new MVP evaluation framework, denoted as \oursys, which lever…

Parallel CPU-GPU Execution for LLM Inference on Constrained GPUs
Jiakun Fan, Yanglin Zhang, Xiangchen Li, Dimitrios S. Nikolopoulos
https://arxiv.org/abs/2506.03296

Parallel CPU-GPU Execution for LLM Inference on Constrained GPUs
Deploying large language models (LLMs) for online inference is often constrained by limited GPU memory, particularly due to the growing KV cache during auto-regressive decoding. Hybrid GPU-CPU execution has emerged as a promising solution by offloading KV cache management and parts of attention computation to the CPU. However, a key bottleneck remains: existing schedulers fail to effectively overlap CPU-offloaded tasks with GPU execution during the latency-critical, bandwidth-bound decode phase…

Remarks on radial symmetry of stationary and uniformly-rotating solutions for the 2D Euler equation
Boquan Fan, Yuchen Wang, Weicheng Zhan
https://arxiv.org/abs/2506.05034

Remarks on radial symmetry of stationary and uniformly-rotating solutions for the 2D Euler equation
We prove that any uniformly rotating solution of the 2D incompressible Euler equation with compactly supported vorticity $ω$ must be radially symmetric whenever its angular velocity satisfies $Ω\in (-\infty,\inf ω/ 2] \cup \, [ \sup ω/ 2, +\infty )$, in both the patch and smooth settings. This result extends the rigidity theorems established in \cite{Gom2021MR4312192} (\textit{Duke Math. J.},170(13):2957-3038, 2021), which were confined to the case of non-positive angular velocities and non…

I have to say I was pleasantly surprised to see how easy Pirate Ship is for getting shipping labels at reduced rates. Their customer service is top-notch. My work had been paying for a shipping provider and I was able to drop their prices considerably.
Not an ad, just a fan of how easy they made #shipping.

Lefschetz morphisms on singular cohomology and local cohomological dimension of toric varieties
Hyunsuk Kim, Sridhar Venkatesh
https://arxiv.org/abs/2506.03026

Lefschetz morphisms on singular cohomology and local cohomological dimension of toric varieties
Given a proper toric variety and a line bundle on it, we describe the morphism on singular cohomology given by the cup product with the Chern class of that line bundle in terms of the data of the associated fan. Using that, we relate the local cohomological dimension of an affine toric variety with the Lefschetz morphism on the singular cohomology of a projective toric variety of one dimension lower. As a corollary, we show that the local cohomological defect is not a combinatorial invariant. W…

Discrete Element Parameter Calibration of Livestock Salt Based on Particle Scaling
Lulu Nie, Baoqin Wen, Jingbin Li, Shufeng Li, Yali Li, Zhaokun Zhang, Zhiyuan Wang, Zhihao Fan
https://arxiv.org/abs/2506.03786

Discrete Element Parameter Calibration of Livestock Salt Based on Particle Scaling
In order to obtain accurate contact parameters for the discrete element simulation of salt particles used in animal husbandry, the principle of particle contact scaling and dimensional analysis were used for particle scaling. Firstly, the Plackett Burman experiment was used to screen the parameters that significantly affect the angle of repose: salt salt rolling friction coefficient, salt salt recovery coefficient, and salt steel rolling friction coefficient. Considering the influence of other …

Den fŸlelse når man er fan af en ny podcast - og så selv bliver inviteret på den! 🤓🎉
https://podcasts.apple.com/dk/podcast/writing-wrongs/id1797795962?l=da

Writing Wrongs
True crime · Månedligt · Every sentence tells a story, every word leaves a trace. Writing Wrongs, from the Aston Institute for Forensic Linguistics, explores historic and contemporary forensic linguistic cases. Hosts Profes...

UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection
Jigang Fan, Quanlin Wu, Shengjie Luo, Liwei Wang
https://arxiv.org/abs/2506.03237

UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection
The detection of ligand binding sites for proteins is a fundamental step in Structure-Based Drug Design. Despite notable advances in recent years, existing methods, datasets, and evaluation metrics are confronted with several key challenges: (1) current datasets and methods are centered on individual protein-ligand complexes and neglect that diverse binding sites may exist across multiple complexes of the same protein, introducing significant statistical bias; (2) ligand binding site detection …

Rounding error analysis of randomized CholeskyQR2 for sparse matrices
Haoran Guan, Yuwei Fan
https://arxiv.org/abs/2506.04208 https://

Rounding error analysis of randomized CholeskyQR2 for sparse matrices
This work focuses on rounding error analysis of randomized CholeskyQR2 (RCholeskyQR2) for sparse matrices. We form RCholeskyQR2 with CholeskyQR2 and matrix sketching in order to accelerate CholeskyQR2 and improve its applicability by compressing the input matrix $X \in \mathbb{R}^{m\times n}$. In many real-world applications, the input matrix $X$ is always sparse. In this work, we follow the model of sparse matrices proposed in \cite{CSparse} and provide an improved rounding error analysis of R…

Large Processor Chip Model
Kaiyan Chang, Mingzhi Chen, Yunji Chen, Zhirong Chen, Dongrui Fan, Junfeng Gong, Nan Guo, Yinhe Han, Qinfen Hao, Shuo Hou, Xuan Huang, Pengwei Jin, Changxin Ke, Cangyuan Li, Guangli Li, Huawei Li, Kuan Li, Naipeng Li, Shengwen Liang, Cheng Liu, Hongwei Liu, Jiahua Liu, Junliang Lv, Jianan Mu, Jin Qin, Bin Sun, Chenxi Wang, Duo Wang, Mingjun Wang, Ying Wang, Chenggang Wu, Peiyang Wu, Teng Wu, Xiao Xiao, Mengyao Xie, Chenwei Xiong, Ruiyuan Xu, Mingyu Yan, Xiaoc…

Large Processor Chip Model
Computer System Architecture serves as a crucial bridge between software applications and the underlying hardware, encompassing components like compilers, CPUs, coprocessors, and RTL designs. Its development, from early mainframes to modern domain-specific architectures, has been driven by rising computational demands and advancements in semiconductor technology. However, traditional paradigms in computer system architecture design are confronting significant challenges, including a reliance on…

Photometric redshift estimation for emission line galaxies of DESI Legacy Imaging Surveys by CNN-MLP
Shirui Wei, Changhua Li, Yanxia Zhang, Chenzhou Cui, Chao Tang, Jingyi Zhang, Yongheng Zhao, Xuebing Wu, Yihan Tao, Dongwei Fan, Shanshan Li, Yunfei Xu, Maoyuan Huang, Xingyu Yang, Zihan Kang, Jinghang Shi
https://arxiv.org/abs/2…

Photometric redshift estimation for emission line galaxies of DESI Legacy Imaging Surveys by CNN-MLP
Emission Line Galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accurac…

Only the Ambidextrous Can Flock: Two-dimensional Chiral Malthusian Flocks, Time crystals, and the KPZ Equation
Leiming Chen, Chiu Fan Lee, John Toner
https://arxiv.org/abs/2506.03488

Only the Ambidextrous Can Flock: Two-dimensional Chiral Malthusian Flocks, Time crystals, and the KPZ Equation
We study two-dimensional chiral dry Malthusian flocks; that is, chiral polar-ordered active matter with neither number nor momentum conservation. In the absence of fluctuations, these form a "time crystal", in which the velocity rotates uniformly at a fixed frequency. Fluctuations are described by the (2+1)-Kardar-Parisi-Zhang (KPZ) equation, which implies short-ranged orientational order. For weak chirality, the system is in the linear regime of the KPZ equation for a wide range of length scal…

All-sky search for individual Primordial Black Hole bursts with LHAASO
Cao, Aharonian, Bai, Bao, Bastieri, Bi, Bi, Bian, Bukevich, Cai, Cao, Cao, Chang, Chang, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Cheng, Cheng, Chu, Cui, Cui, Cui, Cui, Dai, Dai, Dai, , Diao, Dong, Duan, Fan, Fan, Fang, Fang, Fang, Feng, Feng, Feng, Feng, Feng, Feng, Feng, Gabici, Gao, Gao, Gao, Gao, Gao, Ge, Ge, Geng, Giacinti, Gong, Gou, Gu, Guo, Guo, Guo, Guo…

All-sky search for individual Primordial Black Hole bursts with LHAASO
Primordial Black Holes~(PBHs) are hypothetical black holes with a wide range of masses that formed in the early universe. As a result, they may play an important cosmological role and provide a unique probe of the early universe. A PBH with an initial mass of approximately $10^{15}$~g is expected to explode today in a final burst of Hawking radiation. In this work, we conduct an all-sky search for individual PBH burst events using the data collected from March 2021 to July 2024 by the Water Che…

Model Splitting Enhanced Communication-Efficient Federated Learning for CSI Feedback
Yanjie Dong, Haijun Zhang, Gaojie Chen, Xiaoyi Fan, Victor C. M. Leung, Xiping Hu
https://arxiv.org/abs/2506.04113

Model Splitting Enhanced Communication-Efficient Federated Learning for CSI Feedback
Recent advancements have introduced federated machine learning-based channel state information (CSI) compression before the user equipments (UEs) upload the downlink CSI to the base transceiver station (BTS). However, most existing algorithms impose a high communication overhead due to frequent parameter exchanges between UEs and BTS. In this work, we propose a model splitting approach with a shared model at the BTS and multiple local models at the UEs to reduce communication overhead. Moreover…

Electrically tunable quantum interference of atomic spins on surfaces
Hao Wang, Jing Chen, Peng Fan, Yelko del Castillo, Alejandro Ferr\'on, Lili Jiang, Zilong Wu, Shijie Li, Hong-Jun Gao, Heng Fan, Joaqu\'in Fern\'andez-Rossier, Kai Yang
https://arxiv.org/abs/2506.01033

Electrically tunable quantum interference of atomic spins on surfaces
Controlling quantum interference near avoided energy-level crossings is crucial for fast and reliable coherent manipulation in quantum information processing. However, achieving tunable quantum interference in atomically-precise engineered structures remains challenging. Here, we demonstrate electrical control of quantum interference using atomic spins on an insulating film in a scanning tunneling microscope. Using bias voltages applied across the tunnel junction, we modulate the atomically-con…

Moments of the shifted prime divisor function
Mikhail R. Gabdullin
https://arxiv.org/abs/2505.24050 https://arxiv.org/pdf/2505.24050

Moments of the shifted prime divisor function
Let $ω^*(n) = \{d|n: d=p-1, \mbox{$p$ is a prime}\}$. We show that, for each integer $k\geq2$, $$ \sum_{n\leq x}ω^*(n)^k \asymp x(\log x)^{2^k-k-1}, $$ where the implied constant may depend on $k$ only. This confirms a recent conjecture of Fan and Pomerance. Our proof uses a combinatorial identity for the least common multiple, viewed as a multiplicative analogue of the inclusion-exclusion principle, along with analytic tools from number theory.

DS-TTS: Zero-Shot Speaker Style Adaptation from Voice Clips via Dynamic Dual-Style Feature Modulation
Ming Meng, Ziyi Yang, Jian Yang, Zhenjie Su, Yonggui Zhu, Zhaoxin Fan
https://arxiv.org/abs/2506.01020

DS-TTS: Zero-Shot Speaker Style Adaptation from Voice Clips via Dynamic Dual-Style Feature Modulation
Recent advancements in text-to-speech (TTS) technology have increased demand for personalized audio synthesis. Zero-shot voice cloning, a specialized TTS task, aims to synthesize a target speaker's voice using only a single audio sample and arbitrary text, without prior exposure to the speaker during training. This process employs pattern recognition techniques to analyze and replicate the speaker's unique vocal features. Despite progress, challenges remain in adapting to the vocal style of uns…

Superatomic hydrogen: achieving effective aggregation of hydrogen atoms at pressures lower than that of metallic hydrogen
Jia Fan, Chenxi Wan, Rui Liu, Zhen Gong, Hongbo Jing, Baiqiang Liu, Siyang Liu, Zhigang Wang
https://arxiv.org/abs/2506.03463

Superatomic hydrogen: achieving effective aggregation of hydrogen atoms at pressures lower than that of metallic hydrogen
Metal hydrogen exhibiting electron delocalization properties has been recognized as an important prospect for achieving controlled nuclear fusion, but the extreme pressure conditions required exceeding hundreds of GPa remain a daunting challenge. Here, we propose a model of superatomic hydrogen, aiming to reduce the pressure conditions required for the effective aggregation of elemental hydrogen atoms. High-precision ab initio calculations indicate that the pressure required to compress the H13…

Complete universal scaling of first-order phase transitions in the two-dimensional Ising model
Yuxiang Zhang, Fan Zhong
https://arxiv.org/abs/2506.00515 ht…

Complete universal scaling of first-order phase transitions in the two-dimensional Ising model
Phase transitions, as one of the most intriguing phenomena in nature, are divided into first-order phase transitions (FOPTs) and continuous ones in current classification. While the latter shows striking phenomena of scaling and universality, the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic, coarse-grained Landau-Ginzburg theory. Here we apply this theory to a microscopic model -- the paradigmatic Ising model, which undergoes FOPTs bet…

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Haibin Wu, Yuxuan Hu, Ruchao Fan, Xiaofei Wang, Kenichi Kumatani, Bo Ren, Jianwei Yu, Heng Lu, Lijuan Wang, Yao Qian, Jinyu Li
https://arxiv.org/abs/2506.04518

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Speech language models (Speech LMs) enable end-to-end speech-text modelling within a single model, offering a promising direction for spoken dialogue systems. The choice of speech-text jointly decoding paradigm plays a critical role in performance, efficiency, and alignment quality. In this work, we systematically compare representative joint speech-text decoding strategies-including the interleaved, and parallel generation paradigms-under a controlled experimental setup using the same base lan…

Observation of ferron transport in ferroelectrics
Kaiwen Shen, Ping Tang, Xianzhe Chen, Yifan Gao, Yuanfei Fan, Zejing Guo, Yingfen Wei, Hao Jiang, Xumeng Zhang, Ming Wang, Pan He, Wu Shi, Jiahao Han, Yizheng Wu, Jian Shen, Qi Liu, Gerrit E. W. Bauer, Ming Liu
https://arxiv.org/abs/2505.24419

Observation of ferron transport in ferroelectrics
Ferroelectrics feature spontaneous electric dipolar order reconfigurable via electric fields. Recent theoretical studies of the collective excitations of this electric dipolar order give rise to the hope that "ferron" quasiparticles may complement the magnons of magnetic materials in information and heat management technologies. Yet direct experimental evidence of ferron transport remains elusive. Here we demonstrate efficient ferron injection and detection enabled by ferromagnetic metal contac…

Dimension of Besicovitch-Eggleston sets for non-autonomous systems with countable symbolic dynamics
Jonny Imbierski, Charlene Kalle
https://arxiv.org/abs/2506.01803

Dimension of Besicovitch-Eggleston sets for non-autonomous systems with countable symbolic dynamics
In this article we derive a formula for the Hausdorff dimension of Besicovitch-Eggleston level sets associated with non-autonomous dynamics constructed from families of countable affine iterated function systems. The formula obtained shows that the universal-lower-bound phenomenon present in the autonomous case studied by Fan et al. (2010) persists in this non-autonomous setting.

PathGene: Benchmarking Driver Gene Mutations and Exon Prediction Using Multicenter Lung Cancer Histopathology Image Dataset
Liangrui Pan, Qingchun Liang, Shen Zhao, Songqing Fan, Shaoliang Peng
https://arxiv.org/abs/2506.00096

PathGene: Benchmarking Driver Gene Mutations and Exon Prediction Using Multicenter Lung Cancer Histopathology Image Dataset
Accurately predicting gene mutations, mutation subtypes and their exons in lung cancer is critical for personalized treatment planning and prognostic assessment. Faced with regional disparities in medical resources and the high cost of genomic assays, using artificial intelligence to infer these mutations and exon variants from routine histopathology images could greatly facilitate precision therapy. Although some prior studies have shown that deep learning can accelerate the prediction of key …

Diff-FlowFSI: A GPU-Optimized Differentiable CFD Platform for High-Fidelity Turbulence and FSI Simulations
Xiantao Fan, Xinyang Liu, Meng Wang, Jian-Xun Wang
https://arxiv.org/abs/2505.23940

Diff-FlowFSI: A GPU-Optimized Differentiable CFD Platform for High-Fidelity Turbulence and FSI Simulations
Turbulent flows and fluid-structure interactions (FSI) are ubiquitous in scientific and engineering applications, but their accurate and efficient simulation remains a major challenge due to strong nonlinearities, multiscale interactions, and high computational demands. Traditional CFD solvers, though effective, struggle with scalability and adaptability for tasks such as inverse modeling, optimization, and data assimilation. Recent advances in machine learning (ML) have inspired hybrid modelin…

Frequency-Domain Joint Monitoring of Differential Group Delay and Dependent Loss of Optical Singleand Few-Mode Fiber Channels Based on CAZAC Sequences
Linsheng Fan, Gao Ye, Zhongliang Sun, Lingguo Cao, Hao Shi, Jianwei Tang, Shunfeng Wang, Hengying Xu, Chenglin Bai, Jian Zhao, Weisheng Hu, Jinlong Wei
https://arxiv.org/abs/2505.…

Frequency-Domain Joint Monitoring of Differential Group Delay and Dependent Loss of Optical Singleand Few-Mode Fiber Channels Based on CAZAC Sequences
This paper addresses the challenges of monitoring optical-fiber channels subject to complex, multidimensional impairments-such as dynamic interference across polarization or modal dimensions-where conventional methods suffer from high equipment costs, poor impairment discrimination and limited scalability. We propose an in-service, frequency-domain joint monitoring scheme based on constant-amplitude zero-autocorrelation (CAZAC) sequences. Exploiting their flat spectra and ideal autocorrelation,…

Superconducting gaps revealed by STM measurements on La2PrNi2O7 thin films at ambient pressure
Shengtai Fan, Mengjun Ou, Marius Scholten, Qing Li, Zhiyuan Shang, Yi Wang, Jiasen Xu, Huan Yang, Ilya M. Eremin, Hai-Hu Wen
https://arxiv.org/abs/2506.01788

Superconducting gaps revealed by STM measurements on La2PrNi2O7 thin films at ambient pressure
The recent discovery of superconductivity in nickelate systems has generated tremendous interests in the field of superconductivity. The superconducting transition temperature above 80 K in La3Ni2O7 under pressure and the coexisting spin excitations certainly categorize the nickelate superconductors as unconventional. The core issue to understand the superconductivity mechanism is about the superconducting gap and its symmetry. By using the substrate of SrLaAlO4(00l), we have successfully synth…

First systematic experimental 2D mapping of linearly polarized $\gamma$-ray polarimetric distribution in relativistic Compton scattering
Kaijie Chen, Xiangfei Wang, Hanghua Xu, Gongtao Fan, Zirui Hao, Longxiang Liu, Yue Zhang, Sheng Jin, Zhicai Li, Pu Jiao, Qiankun Sun, Zhenwei Wang, Mengdie Zhou, Mengke Xu, Hongwei Wang, Wenqing Shen, Yugang Ma
http…

First systematic experimental 2D mapping of linearly polarized $γ$-ray polarimetric distribution in relativistic Compton scattering
The interaction of photons with relativistic electrons constitutes a fundamental electromagnetic process whose polarization transfer mechanics remain incompletely characterized. We report the first systematic measurement of spatial polarization distribution for $γ$-rays generated via \SI{45}{\degree} slant inverse Compton scattering (ICS) between linearly polarized \SI{0.117}{\eV} photons and \SI{3.5}{\GeV} electrons, performing full 2D mapping of intensity, polarization angle (AOP), and degre…

A Tree-guided CNN for image super-resolution
Chunwei Tian, Mingjian Song, Xiaopeng Fan, Xiangtao Zheng, Bob Zhang, David Zhang
https://arxiv.org/abs/2506.02585

A Tree-guided CNN for image super-resolution
Deep convolutional neural networks can extract more accurate structural information via deep architectures to obtain good performance in image super-resolution. However, it is not easy to find effect of important layers in a single network architecture to decrease performance of super-resolution. In this paper, we design a tree-guided CNN for image super-resolution (TSRNet). It uses a tree architecture to guide a deep network to enhance effect of key nodes to amplify the relation of hierarchica…

Cognitive-Radio Functionality: A Novel Configuration for STAR-RIS assisted RSMA Networks
Saeed Ibrahim, Yue Xiao, Dimitrios Tyrovolas, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Zheng Ma, George K. Karagiannidis, Pinghzi Fan
https://arxiv.org/abs/2505.24583

Cognitive-Radio Functionality: A Novel Configuration for STAR-RIS assisted RSMA Networks
Cognitive radio rate-splitting multiple access (CR-RSMA) has emerged as a promising multiple access framework that can efficiently manage interference and adapt dynamically to heterogeneous quality-of-service (QoS) requirements. To effectively support such demanding access schemes, programmable wireless environments have attracted considerable attention, especially through simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs), which can enable full-space con…

MMM4Rec: An Transfer-Efficient Framework for Multi-modal Sequential Recommendation
Hao Fan, Yanrong Hu, Kai Fang, Qingyang Liu, Hongjiu Liu
https://arxiv.org/abs/2506.02916

MMM4Rec: An Transfer-Efficient Framework for Multi-modal Sequential Recommendation
Sequential Recommendation (SR) systems model user preferences by analyzing interaction histories. Although transferable multi-modal SR architectures demonstrate superior performance compared to traditional ID-based approaches, current methods incur substantial fine-tuning costs when adapting to new domains due to complex optimization requirements and negative transfer effects - a significant deployment bottleneck that hinders engineers from efficiently repurposing pre-trained models for novel a…

Offline Map Matching Based on Localization Error Distribution Modeling
Ruilin Xu, Yuchen Song, Kaijie Li, Xitong Gao, Kejiang Ye, Fan Zhang, Juanjuan Zhao
https://arxiv.org/abs/2505.23123

Offline Map Matching Based on Localization Error Distribution Modeling
Offline map matching involves aligning historical trajectories of mobile objects, which may have positional errors, with digital maps. This is essential for applications in intelligent transportation systems (ITS), such as route analysis and traffic pattern mining. Existing methods have two main limitations: (i) they assume a uniform Localization Error Distribution (LED) across urban areas, neglecting environmental factors that lead to suboptimal path search ranges, and (ii) they struggle to ef…

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Tinghuan Li, Shuheng Chen, Junyi Fan, Elham Pishgar, Kamiar Alaei, Greg Placencia, Maryam Pishgar
https://arxiv.org/abs/2506.03209

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
Postoperative stroke remains a critical complication in elderly surgical intensive care unit (SICU) patients, contributing to prolonged hospitalization, elevated healthcare costs, and increased mortality. Accurate early risk stratification is essential to enable timely intervention and improve clinical outcomes. We constructed a combined cohort of 19,085 elderly SICU admissions from the MIMIC-III and MIMIC-IV databases and developed an interpretable machine learning (ML) framework to predict in…

Sums and differences of sets: a further improvement over AlphaEvolve
Fan Zheng
https://arxiv.org/abs/2506.01896 https://arxiv.org/pdf…

Sums and differences of sets: a further improvement over AlphaEvolve
We present a new advancement in the sum and difference of sets problem, which improves upon recent results by both DeepMind's AlphaEvolve ($θ= 1.1584$) and subsequent explicit constructions ($θ= 1.173050$). In this work, we construct a sequence of $U$ sets which in the limit establishes a new lower bound of $θ= 1.173077$.

Heterodyne detection of low-frequency fields via Rydberg EIT with phase demodulation
Shenchao Jin, Xiayang Fan, Xin Wang, Yi Song, Yuan Sun
https://arxiv.org/abs/2505.24268

As a former Pebble user (and a big fan of the whole concept) I'm looking at this with interest. At the same time though, this very project killed my interest in any hardware project funded on Kickstarter, so I have trust issues.
https://store.repebble.com/countdown

Two-Phase Treatment with Noncompliance: Identifying the Cumulative Average Treatment Effect via Multisite Instrumental Variables
Guanglei Hong, Xu Qin, Zhengyan Xu, Fan Yang
https://arxiv.org/abs/2506.03104

Two-Phase Treatment with Noncompliance: Identifying the Cumulative Average Treatment Effect via Multisite Instrumental Variables
In evaluating a multi-phase intervention, the cumulative average treatment effect (ATE) is often the causal estimand of key interest. Yet some individuals who do not respond well to the Phase-I treatment may subsequently display noncompliant behaviors. However, noncompliance tends to be constrained by the stochastic availability of slots under the alternative treatment condition in Phase II, which makes the notion of the "complier average treatment effect" problematic. Moreover, the Phase-I tre…

The Wave Equation in the Context of Reduced Groups $C^*$-Algebras
Fan Huang
https://arxiv.org/abs/2505.22930 https://arxiv.org/pdf/25…

The Wave Equation in the Context of Reduced Groups $C^*$-Algebras
Motivated by the identification $C(\mathbb{T})\cong C_r^*(\mathbb{Z})$ and the wave equation on the circle, we explore the wave equation in the context of reduced group $C^*$-algebras $C_r^*(G)$ for countably infinite, possibly non-abelian groups $G$. Using a one-parameter group of $*$-automorphisms whose infinitesimal generator paves the way to an analogue of the Laplacian, we establish the existence and uniqueness of solutions to the wave equation within this framework.

Exponential Riesz basis in non-Archimedean locally compact Abelian group
Aihua Fan, Shilei Fan
https://arxiv.org/abs/2505.21310 https://

Exponential Riesz basis in non-Archimedean locally compact Abelian group
This paper establishes two fundamental results on the existence of exponential Riesz basis on non-Archimedean locally compact Abelian groups: the existence of Riesz basis of exponentials for all finite unions of balls and the non-existence of such basis for some bounded sets.

Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization
Hao Mark Chen, Zehuan Zhang, Wanru Zhao, Nicholas Lane, Hongxiang Fan
https://arxiv.org/abs/2506.00002

Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization
Recent years have witnessed a significant increase in the adoption of AI techniques to enhance electronic design automation. In particular, the emergence of Large Language Models (LLMs) has sparked significant interest in LLM-assisted hardware design generation, spanning applications from classical digital circuits to quantum computing. Despite substantial progress in this direction, the quality of LLM-generated hardware design still cannot meet the requirements for practical deployment. In thi…

RPRA-ADD: Forgery Trace Enhancement-Driven Audio Deepfake Detection
Ruibo Fu, Xiaopeng Wang, Zhengqi Wen, Jianhua Tao, Yuankun Xie, Zhiyong Wang, Chunyu Qiang, Xuefei Liu, Cunhang Fan, Chenxing Li, Guanjun Li
https://arxiv.org/abs/2506.00375

RPRA-ADD: Forgery Trace Enhancement-Driven Audio Deepfake Detection
Existing methods for deepfake audio detection have demonstrated some effectiveness. However, they still face challenges in generalizing to new forgery techniques and evolving attack patterns. This limitation mainly arises because the models rely heavily on the distribution of the training data and fail to learn a decision boundary that captures the essential characteristics of forgeries. Additionally, relying solely on a classification loss makes it difficult to capture the intrinsic difference…

Align-DA: Align Score-based Atmospheric Data Assimilation with Multiple Preferences
Jing-An Sun, Hang Fan, Junchao Gong, Ben Fei, Kun Chen, Fenghua Ling, Wenlong Zhang, Wanghan Xu, Li Yan, Pierre Gentine, Lei Bai
https://arxiv.org/abs/2505.22008

Align-DA: Align Score-based Atmospheric Data Assimilation with Multiple Preferences
Data assimilation (DA) aims to estimate the full state of a dynamical system by combining partial and noisy observations with a prior model forecast, commonly referred to as the background. In atmospheric applications, this problem is fundamentally ill-posed due to the sparsity of observations relative to the high-dimensional state space. Traditional methods address this challenge by simplifying background priors to regularize the solution, which are empirical and require continual tuning for a…

Phi-Omni-ST: A multimodal language model for direct speech-to-speech translation
Yuxuan Hu, Haibin Wu, Ruchao Fan, Xiaofei Wang, Heng Lu, Yao Qian, Jinyu Li
https://arxiv.org/abs/2506.04392

Phi-Omni-ST: A multimodal language model for direct speech-to-speech translation
Speech-aware language models (LMs) have demonstrated capabilities in understanding spoken language while generating text-based responses. However, enabling them to produce speech output efficiently and effectively remains a challenge. In this paper, we present Phi-Omni-ST, a multimodal LM for direct speech-to-speech translation (ST), built on the open-source Phi-4 MM model. Phi-Omni-ST extends its predecessor by generating translated speech using an audio transformer head that predicts audio to…

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
Marcos V. Conde, Radu Timofte, Zihao Lu, Xiangyu Kongand Xiaoxia Xingand Fan Wangand Suejin Hanand MinKyu Parkand Tianyu Zhangand Xin Luoand Yeda Chenand Dong Liuand Li Pangand Yuhang Yangand Hongzhong Wangand Xiangyong Caoand Ruixuan Jiangand Senyan Xuand Siyuan Jiangand Xueyang Fuand Zheng-Jun Zhaand Tianyu Haoand Yuhong Heand Ruoqi Liand Yueqi Yangand Xiang Yuand Guanlan Hongand Minmin Yiand Yuanjia Chenand Liwen Zha…

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the…

Gone with the Wind: JWST-MIRI Unveils a Strong Outflow from the Quiescent Stellar-Mass Black Hole A0620-00
Zihao Zuo, Gabriele Cugno, Joseph Michail, Elena Gallo, David M. Russell, Richard M. Plotkin, Fan Zou, M. Cristina Baglio, Piergiorgio Casella, Fraser J. Cowie, Rob Fender, Poshak Gandhi, Sera Markoff, Federico Vincentelli, Fraser Lewis, Jon M. Miller, James C. A. Miller-Jones, Alexandra Veledina

Gone with the Wind: JWST-MIRI Unveils a Strong Outflow from the Quiescent Stellar-Mass Black Hole A0620-00
We present new observations of the black hole X-ray binary A0620-00 using the Mid-Infrared Instrument on the James Webb Space Telescope, during a state where the X-ray luminosity is 9 orders of magnitude below Eddington, and coordinated with radio, near-infrared and optical observations. The goal is to understand the nature of the excess mid-infrared (MIR) emission originally detected by Spitzer red-ward of 8 $μ$m. The stellar-subtracted MIR spectrum is well-modeled by a power law with a spect…

A continuum mechanics approach for the deformation of non-Euclidean origami generated by piecewise constant nematic director fields
Linjuan Wang, Fan Feng
https://arxiv.org/abs/2506.01309

A continuum mechanics approach for the deformation of non-Euclidean origami generated by piecewise constant nematic director fields
We merge classical origami concepts with active actuation by designing origami patterns whose panels undergo prescribed metric changes. These metric changes render the system non-Euclidean, inducing non-zero Gaussian curvature at the vertices after actuation. Such patterns can be realized by programming piecewise constant director fields in liquid crystal elastomer (LCE) sheets. In this work, we address the geometric design of both compatible reference director patterns and their corresponding …

Real-time Light Curve Classification Framework for the Wide Field Survey Telescope Using Modified Semi-supervised Variational Auto-Encoder
Yongling Tang, Lulu Fan, Zhen Wan, Yating Liu, Yan Lu
https://arxiv.org/abs/2506.01216

Real-time Light Curve Classification Framework for the Wide Field Survey Telescope Using Modified Semi-supervised Variational Auto-Encoder
Modern time-domain astronomy will benefit from the vast data collected by survey telescopes. The 2.5 m Wide Field Survey Telescope (WFST), with its powerful capabilities, is promising to make significant contributions in the era of large sky surveys. To harness the full potential of the enormous amount of unlabeled light curve data that the WFST will collect, we have developed a semisupervised light curve classification framework. This framework showcases several unique features. First, it is o…

The $M_{\rm BH}-M_\star$ Relation of the hyperluminous Dust-obscured Quasars up to $z \sim 4$
Yibin Luo, Lulu Fan, Weibin Sun, Haoran Yu, Yunkun Han, Guangwen Chen, Mengqiu Huang, Yihang Zhang, Zheyu Lin
https://arxiv.org/abs/2506.01218

The $M_{\rm BH}-M_\star$ Relation of the hyperluminous Dust-obscured Quasars up to $z \sim 4$
Hot dust-obscured galaxies (Hot DOGs) are a rare population of hyperluminous dust-obscured quasars discovered by the Wide-field Infrared Survey Explorer (WISE) all-sky survey. The heavy circumnuclear dust obscuration allows only a small amount of scattered light from the obscured quasar to escape, enabling the decomposition of the stellar component from the total flux. The presence of scattered light enables the redshift of the source and the properties of the black hole to be obtained from SDS…

Combinatorial $t$-Designs from Finite Abelian Groups and Their Applications to Elliptic Curve Codes
Hengfeng Liu, Chunming Tang, Cuiling Fan, Rong Luo
https://arxiv.org/abs/2506.00429

Combinatorial $t$-Designs from Finite Abelian Groups and Their Applications to Elliptic Curve Codes
In this paper, we establish the conditions for some finite abelian groups and the family all the $k$-sets in each of them summing up to an element $x$ to form $t$-designs. We fully characterize the sufficient and necessary conditions for the incidence structures to form $1$-designs in finite abelian $p$-groups, generalizing existing results on vector spaces over finite fields. For finite abelian groups of exponent $pq$, we also propose sufficient and necessary conditions for the incidence struc…

Floquet M\"obius topological insulators
Longwen Zhou, Fan Zhang, Jiaxin Pan
https://arxiv.org/abs/2506.01401 https://arxiv.org/p…

Floquet Möbius topological insulators
Möbius topological insulators hold twofold-degenerated dispersive edge bands with Möbius twists in momentum space, which are protected by the combination of chiral and ${\mathbb Z}_2$-projective translational symmetries. In this work, we reveal a unique type of Möbius topological insulator, whose edge bands could twist around the quasienergy $π$ of a periodically driven system and are thus of Floquet origin. By applying time-periodic quenches to an experimentally realized Möbius insulator …

TRiMM: Transformer-Based Rich Motion Matching for Real-Time multi-modal Interaction in Digital Humans
Yueqian Guo, Tianzhao Li, Xin Lyu, Jiehaolin Chen, Zhaohan Wang, Sirui Xiao, Yurun Chen, Yezi He, Helin Li, Fan Zhang
https://arxiv.org/abs/2506.01077

TRiMM: Transformer-Based Rich Motion Matching for Real-Time multi-modal Interaction in Digital Humans
Large Language Model (LLM)-driven digital humans have sparked a series of recent studies on co-speech gesture generation systems. However, existing approaches struggle with real-time synthesis and long-text comprehension. This paper introduces Transformer-Based Rich Motion Matching (TRiMM), a novel multi-modal framework for real-time 3D gesture generation. Our method incorporates three modules: 1) a cross-modal attention mechanism to achieve precise temporal alignment between speech and gesture…

A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
Jakub Martinka, Lina Zhang, Yi-Fan Hou, Miko{\l}aj Martyka, Ji\v{r}\'i Pittner, Mario Barbatti, Pavlo O. Dral
https://arxiv.org/abs/2505.23344

A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
Nonadiabatic couplings (NACs) play a crucial role in modeling photochemical and photophysical processes with methods such as the widely used fewest-switches surface hopping (FSSH). There is therefore a strong incentive to machine learn NACs for accelerating simulations. However, this is challenging due to NACs' vectorial, double-valued character and the singularity near a conical intersection seam. For the first time, we design NAC-specific descriptors based on our domain expertise and show tha…

Ocean-E2E: Hybrid Physics-Based and Data-Driven Global Forecasting of Extreme Marine Heatwaves with End-to-End Neural Assimilation
Ruiqi Shu, Yuan Gao, Hao Wu, Ruijian Gou, Yanfei Xiang, Fan Xu, Qingsong Wen, Xian Wu, Xiaomeng Huang
https://arxiv.org/abs/2505.22071

Ocean-E2E: Hybrid Physics-Based and Data-Driven Global Forecasting of Extreme Marine Heatwaves with End-to-End Neural Assimilation
This work focuses on the end-to-end forecast of global extreme marine heatwaves (MHWs), which are unusually warm sea surface temperature events with profound impacts on marine ecosystems. Accurate prediction of extreme MHWs has significant scientific and financial worth. However, existing methods still have certain limitations, especially in the most extreme MHWs. In this study, to address these issues, based on the physical nature of MHWs, we created a novel hybrid data-driven and numerical MH…

On the Scaling of Robustness and Effectiveness in Dense Retrieval
Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng
https://arxiv.org/abs/2505.24279 …

On the Scaling of Robustness and Effectiveness in Dense Retrieval
Robustness and Effectiveness are critical aspects of developing dense retrieval models for real-world applications. It is known that there is a trade-off between the two. Recent work has addressed scaling laws of effectiveness in dense retrieval, revealing a power-law relationship between effectiveness and the size of models and data. Does robustness follow scaling laws too? If so, can scaling improve both robustness and effectiveness together, or do they remain locked in a trade-off? To answ…

Halfway to induced saturation for even cycles
Xinyue Fan, Sahab Hajebi, Sepehr Hajebi, Sophie Spiral
https://arxiv.org/abs/2505.24100 https://

Halfway to induced saturation for even cycles
For graphs $G$ and $H$, we say that $G$ is $H$-free if no induced subgraph of $G$ is isomorphic to $H$, and that $G$ is $H$-induced saturated if $G$ is $H$-free but removing or adding any edge in $G$ creates an induced copy of $H$. A full characterization of graphs $H$ for which $H$-induced saturated graphs exist remains elusive. Even the case where $H$ is a path -- now settled by the collective results of Martin and Smith, Bonamy et al., and Dvoŕǎk -- was already quite challenging. What if…

Quantitative analysis of cell size control mechanisms
Shuqi Fan, Jinzhi Lei
https://arxiv.org/abs/2505.19416 https://arxiv.org/pdf/25…

Quantitative analysis of cell size control mechanisms
Cell size control is crucial for maintaining cellular function and homeostasis. In this study, we develop a first-order partial differential equation model to examine the effects of three key size control mechanisms: the sizer, timer, and adder. Each mechanism is incorporated into the model through distinct boundary conditions. Exact solutions for these mechanisms are derived using the method of characteristics, allowing us to explore how the steady-state size distribution depends on control pa…

Optical Photometric Monitoring of the Blazar OT 355 and Local Standard Stars' Calibration
R. Bachev, Tushar Tripathi, Alok C. Gupta, A. Kurtenkov, Y. Nikolov, A. Strigachev, S. Boeva, G. Latev, B. Spassov, M. Minev, E. Ovcharov, W. -X. Yang, Yi Liu, J. -H. Fan
https://arxiv.org/abs/2505.23677…

Optical Photometric Monitoring of the Blazar OT 355 and Local Standard Stars' Calibration
OT 355 (4FGL J1734.3 + 3858) is a relatively rarely studied but highly variable, moderate-redshift (z = 0.975) flat-spectrum radio quasar (blazar). With this work, we aim to study its optical variability on different timescales, which can help us to better understand the physical processes in relativistic jets operating in blazar-type active galactic nuclei. OT 355 was observed in four colors (BVRI) during 41 nights between 2017 and 2023 using three 1 and 2 m class telescopes. The object was al…

M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
Cunhang Fan, Ying Chen, Jian Zhou, Zexu Pan, Jingjing Zhang, Youdian Gao, Xiaoke Yang, Zhengqi Wen, Zhao Lv
https://arxiv.org/abs/2506.00466

M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
The brain-assisted target speaker extraction (TSE) aims to extract the attended speech from mixed speech by utilizing the brain neural activities, for example Electroencephalography (EEG). However, existing models overlook the issue of temporal misalignment between speech and EEG modalities, which hampers TSE performance. In addition, the speech encoder in current models typically uses basic temporal operations (e.g., one-dimensional convolution), which are unable to effectively extract target …

Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
Chen Liu, Mingchen Li, Yang Tan, Wenrui Gou, Guisheng Fan, Bingxin Zhou
https://arxiv.org/abs/2505.20301

Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
A pivotal area of research in antibody engineering is to find effective modifications that enhance antibody-antigen binding affinity. Traditional wet-lab experiments assess mutants in a costly and time-consuming manner. Emerging deep learning solutions offer an alternative by modeling antibody structures to predict binding affinity changes. However, they heavily depend on high-quality complex structures, which are frequently unavailable in practice. Therefore, we propose ProtAttBA, a deep learn…

Response to the comment on The inconvenient truth about flocks by Chat\'e and Solon
Leiming Chen, Patrick Jentsch, Chiu Fan Lee, Ananyo Maitra, Sriram Ramaswamy, John Toner
https://arxiv.org/abs/2505.21602

Response to the comment on The inconvenient truth about flocks by Chaté and Solon
This is our response to the comment arXiv:2504.13683 posted by Chaté and Solon in reference to our preprint arXiv:2503.17064

Fluid Simulation on Vortex Particle Flow Maps
Sinan Wang, Junwei Zhou, Fan Feng, Zhiqi Li, Yuchen Sun, Duowen Chen, Greg Turk, Bo Zhu
https://arxiv.org/abs/2505.21946

Fluid Simulation on Vortex Particle Flow Maps
We propose the Vortex Particle Flow Map (VPFM) method to simulate incompressible flow with complex vortical evolution in the presence of dynamic solid boundaries. The core insight of our approach is that vorticity is an ideal quantity for evolution on particle flow maps, enabling significantly longer flow map distances compared to other fluid quantities like velocity or impulse. To achieve this goal, we developed a hybrid Eulerian-Lagrangian representation that evolves vorticity and flow map qu…