Tootfinder

Faster and Better: Reinforced Collaborative Distillation and Self-Learning for Infrared-Visible Image Fusion
Yuhao Wang, Lingjuan Miao, Zhiqiang Zhou, Yajun Qiao, Lei Zhang
https://arxiv.org/abs/2509.02424

Faster and Better: Reinforced Collaborative Distillation and Self-Learning for Infrared-Visible Image Fusion
Infrared and visible image fusion plays a critical role in enhancing scene perception by combining complementary information from different modalities. Despite recent advances, achieving high-quality image fusion with lightweight models remains a significant challenge. To bridge this gap, we propose a novel collaborative distillation and self-learning framework for image fusion driven by reinforcement learning. Unlike conventional distillation, this approach not only enables the student model t…

GPS-DRIFT: Marine Surface Robot Localization using IMU-GPS Fusion and Invariant Filtering
Surya Pratap Singh, Tsimafei Lazouski, Maani Ghaffari
https://arxiv.org/abs/2507.02198

GPS-DRIFT: Marine Surface Robot Localization using IMU-GPS Fusion and Invariant Filtering
This paper presents an extension of the DRIFT invariant state estimation framework, enabling robust fusion of GPS and IMU data for accurate pose and heading estimation. Originally developed for testing and usage on a marine autonomous surface vehicle (ASV), this approach can also be utilized on other mobile systems. Building upon the original proprioceptive only DRIFT algorithm, we develop a symmetry-preserving sensor fusion pipeline utilizing the invariant extended Kalman filter (InEKF) to int…

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion
Xin Guan, PeiHsin Lin, Zekun Wu, Ze Wang, Ruibo Zhang, Emre Kazim, Adriano Koshiyama
https://arxiv.org/abs/2507.02595

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion
Multiperspective Fusion (MPF) is a novel posttraining alignment framework for large language models (LLMs) developed in response to the growing need for easy bias mitigation. Built on top of the SAGED pipeline, an automated system for constructing bias benchmarks and extracting interpretable baseline distributions, MPF leverages multiperspective generations to expose and align biases in LLM outputs with nuanced, humanlike baselines. By decomposing baseline, such as sentiment distributions from …

Public perspectives on the design of fusion energy facilities
Nathan Kawamoto, Daniel Hoover, Jonathan Xie, Jacob Walters, Katie Snyder, Aditi Verma
https://arxiv.org/abs/2507.02207

Public perspectives on the design of fusion energy facilities
As fusion energy technologies approach demonstration and commercial deployment, understanding public perspectives on future fusion facilities will be critical for achieving social license, especially because fusion energy facilities, unlike large fission reactors, may be sited in closer proximity to people and communities, due to distinct regulatory frameworks. In a departure from the 'decide-announce-defend' approach typically used to site energy infrastructure, we develop a participatory desi…

Modular fusion categories with few twists
Andrew Schopieray
https://arxiv.org/abs/2509.02501 https://arxiv.org/pdf/2509.02501

Modular fusion categories with few twists
We classify modular fusion categories up to braided equivalence with less than four distinct twists of simple objects by observing that under this assumption, for each positive integer $N$, there are finitely many modular fusion categories of Frobenius-Schur exponent $N$ up to braided equivalence whose twists are a proper subset of the $N^\mathrm{th}$ roots of unity.

HyDeFuse: Provably Convergent Denoiser-Driven Hyperspectral Fusion
Sagar Kumar, Unni V S, Kunal Narayan Chaudhury
https://arxiv.org/abs/2509.02477 https://…

HyDeFuse: Provably Convergent Denoiser-Driven Hyperspectral Fusion
Hyperspectral (HS) images provide fine spectral resolution but have limited spatial resolution, whereas multispectral (MS) images capture finer spatial details but have fewer bands. HS-MS fusion aims to integrate HS and MS images to generate a single image with improved spatial and spectral resolution. This is commonly formulated as an inverse problem with a linear forward model. However, reconstructing high-quality images using the forward model alone is challenging, necessitating the use of r…

Seit den 1960ern kommt die #Kernfusion in 30 bis 40 Jahren. 🤪
#Google investiert in #Kernfusion und will künftig 200 Megawatt Strom vom Start-up CFS beziehen.
Doch die Technologie wird…

Google bets on fusion power as its greenhouse gas emissions grow
Google has agreed to purchase electricity from a nuclear fusion power plant, but the technology still has to prove that it’s commercially feasible. 

Parton-shower and fixed-order QCD effects in Higgs-boson production in weak-boson fusion and its decays to bottom quarks
Arnd Behring, Kirill Melnikov, Ivan Novikov, Giulia Zanderighi
https://arxiv.org/abs/2507.01448

Parton-shower and fixed-order QCD effects in Higgs-boson production in weak-boson fusion and its decays to bottom quarks
Recently, it was observed [arXiv:2407.09363] that an aggressive cut on the $b$-jets' transverse momenta applied to Higgs-boson production in weak-boson fusion followed by the decay $H \to b \bar b$, leads to very large QCD corrections to the fiducial cross section. In this paper we show that these corrections are caused by soft and collinear QCD radiation and, therefore, can be efficiently treated by a parton shower. We combine the parton-shower description of the decay $H \to b \bar b$ with NN…

Google made an agreement to buy half of the output of CFS's first fusion plant; about 200MW; sometime 'in the early 2030's.
(Microsoft have an agreement for one of Helion's fusion reactors which is 50MW and supposedly before 2030).
CFS does fairly conventional Tokamaks (albeit with HTS superconducotrs, so vastly smaller than ITER)

Google and Commonwealth Fusion Systems Sign Strategic Partnership
The world's largest and leading commercial fusion energy company

Insight-LLM: LLM-enhanced Multi-view Fusion in Insider Threat Detection
Chengyu Song, Jianming Zheng
https://arxiv.org/abs/2509.01509 https://arxiv.org/pdf…

Insight-LLM: LLM-enhanced Multi-view Fusion in Insider Threat Detection
Insider threat detection (ITD) requires analyzing sparse, heterogeneous user behavior. Existing ITD methods predominantly rely on single-view modeling, resulting in limited coverage and missed anomalies. While multi-view learning has shown promise in other domains, its direct application to ITD introduces significant challenges: scalability bottlenecks from independently trained sub-models, semantic misalignment across disparate feature spaces, and view imbalance that causes high-signal modalit…

TAGF: Time-aware Gated Fusion for Multimodal Valence-Arousal Estimation
Yubeen Lee, Sangeun Lee, Chaewon Park, Junyeop Cha, Eunil Park
https://arxiv.org/abs/2507.02080

TAGF: Time-aware Gated Fusion for Multimodal Valence-Arousal Estimation
Multimodal emotion recognition often suffers from performance degradation in valence-arousal estimation due to noise and misalignment between audio and visual modalities. To address this challenge, we introduce TAGF, a Time-aware Gated Fusion framework for multimodal emotion recognition. The TAGF adaptively modulates the contribution of recursive attention outputs based on temporal dynamics. Specifically, the TAGF incorporates a BiLSTM-based temporal gating mechanism to learn the relative impor…

Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations
Bohao Wang, Zitao Shuai, Fenghao Zhu, Chongwen Huang, Yongliang Shen, Zhaoyang Zhang, Qianqian Yang, Sami Muhaidat, Merouane Debbah
https://arxiv.org/abs/2507.01337

Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations
Multimodal fingerprinting is a crucial technique to sub-meter 6G integrated sensing and communications (ISAC) localization, but two hurdles block deployment: (i) the contribution each modality makes to the target position varies with the operating conditions such as carrier frequency, and (ii) spatial and fingerprint ambiguities markedly undermine localization accuracy, especially in non-line-of-sight (NLOS) scenarios. To solve these problems, we introduce SCADF-MoE, a spatial-context aware dyn…

3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP
Ranjan Sapkota, Zhichao Meng, Martin Churuvija, Xiaoqiang Du, Zenghong Ma, Manoj Karkee
https://arxiv.org/abs/2507.01912

3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP
In orchard automation, dense foliage during the canopy season severely occludes tree structures, minimizing visibility to various canopy parts such as trunks and branches, which limits the ability of a machine vision system. However, canopy structure is more open and visible during the dormant season when trees are defoliated. In this work, we present an information fusion framework that integrates multi-seasonal structural data to support robotic and automated crop load management during the e…

Experimental and simulative study on laser irradiation of 3D-printed micro-structures at intensities relevant for inertial confinement fusion
M. Cipriani, F. Consoli, M. Scisci\`o, A. Solovjovas, I. A. Petsi, M. Malinauskas, P. Andreoli, G. Cristofari, E. Di Ferdinando, G. Di Giorgio
https://arxiv.org/abs/2506.04017

Experimental and simulative study on laser irradiation of 3D-printed micro-structures at intensities relevant for inertial confinement fusion
Inertial confinement fusion requires a constant search for the most effective materials for improving the efficiency of the compression of the capsule and of the laser-to-target energy transfer. Foams could provide a solution to these problems, but they require further experimental and theoretical investigation. The new 3D-printing technologies, such as the two-photon polymerization, are opening a new era in the production of foams, allowing for the fine control of the material morphology. Deta…

Nuclear fusion plasma fuelling with ice pellets using a neuromorphic controller
L. L. T. C. Jansen, E. Petri, M. van Berkel, W. P. M. H. Heemels
https://arxiv.org/abs/2509.02147

Nuclear fusion plasma fuelling with ice pellets using a neuromorphic controller
In reactor-grade tokamaks, pellet injection is the best candidate for core plasma fuelling. However, density control schemes that can handle the hybrid nature of this type of fuelling, i.e., the discrete impact of the pellets on the continuously evolving plasma density, are lacking. This paper proposes a neuromorphic controller, inspired by the integrate-and-fire neuronal model, to address this problem. The overall system is modelled as a hybrid system, and we analyse the proposed controller in…

Fusion of Modulation Spectrogram and SSL with Multi-head Attention for Fake Speech Detection
Rishith Sadashiv T N, Abhishek Bedge, Saisha Suresh Bore, Jagabandhu Mishra, Mrinmoy Bhattacharjee, S R Mahadeva Prasanna
https://arxiv.org/abs/2508.01034

Fusion of Modulation Spectrogram and SSL with Multi-head Attention for Fake Speech Detection
Fake speech detection systems have become a necessity to combat against speech deepfakes. Current systems exhibit poor generalizability on out-of-domain speech samples due to lack to diverse training data. In this paper, we attempt to address domain generalization issue by proposing a novel speech representation using self-supervised (SSL) speech embeddings and the Modulation Spectrogram (MS) feature. A fusion strategy is used to combine both speech representations to introduce a new front-end …

US lab's new pellet injector powers record fusion breakthrough, sustaining high-performance plasma for 43 seconds at Wendelstein 7-X stellarator. Major step in fusion energy research! #climatechange #climatesolutions

New pellet injector from US lab powers fusion record breakthrough
A new fuel pellet injector developed by ORNL has helped scientists sustain a fusion plasma for a record 43 seconds.

Tables of practical invariants for distinguishing multiplicity-free fusion categories up to rank 7
Gert Vercleyen
https://arxiv.org/abs/2507.00652 https://…

Tables of practical invariants for distinguishing multiplicity-free fusion categories up to rank 7
This paper discusses to what extent the census of multiplicity-free fusion categories up to rank 7, proposed by the software package Anyonica and the anyonwiki website, can be regarded as a proper classification. The questions of correctness and completeness are briefly discussed, and the question of inequivalence of the provided categories is resolved under the assumption that all proposed data is correct. This is done by providing tables of small sets of invariants for these categories, for w…

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts.
TL;DR: Solar sails could make the trip take some 7 years, while thermonuclear fusion could take 10 years. Whereas with current engines it would take 30 years.
https://arxiv.org/abs/2506.17732

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts
Exploring the outer reaches of the Solar System presents significant propulsion and mission design challenges. This study assesses the feasibility of a mission to Sedna using two advanced propulsion concepts: the Direct Fusion Drive (DFD) rocket engine, based on D-$^{3}$He thermonuclear fusion, and a solar sail utilizing thermal desorption of its coating for propulsion. Both are evaluated for a one-way Earth-to-Sedna mission; however, due to the different performances the DFD would enable orbit…

Anti-scatter grid prototype manufactured via laser powder bed fusion of pure tungsten
I. Diachkov, S. Chernyshikhin, S. Dadabaev, S. Kholodenko, A. Kulik, V. Obraztsov, E. Shmanin, D. Strekalina
https://arxiv.org/abs/2509.03255

Anti-scatter grid prototype manufactured via laser powder bed fusion of pure tungsten
This paper describes the production and tests performed with the tungsten collimator prototype produced using laser powder bed fusion technology in a converging geometry. This prototype has been tested for being the anti-scatter grid for X-ray imaging to reduce background from the scattered photons. The purpose is reducing patient radiation exposure in medical applications. Obtained results are positive, grid provides definitive enhancement in marker detection which proves to be especially usef…

A Late Collaborative Perception Framework for 3D Multi-Object and Multi-Source Association and Fusion
Maryem Fadili (VeDeCom, IRSEEM), Mohamed Anis Ghaoui (VeDeCom), Louis Lecrosnier (IRSEEM, ESIGELEC), Steve Pechberti (VeDeCom), Redouane Khemmar (IRSEEM, ESIGELEC, IRSEEM)
https://arxiv.org/abs/2507.02430

A Late Collaborative Perception Framework for 3D Multi-Object and Multi-Source Association and Fusion
In autonomous driving, recent research has increasingly focused on collaborative perception based on deep learning to overcome the limitations of individual perception systems. Although these methods achieve high accuracy, they rely on high communication bandwidth and require unrestricted access to each agent's object detection model architecture and parameters. These constraints pose challenges real-world autonomous driving scenarios, where communication limitations and the need to safeguard p…

Multi-Branch DNN and CRLB-Ratio-Weight Fusion for Enhanced DOA Sensing via a Massive H$^2$AD MIMO Receiver
Feng Shu, Jiatong Bai, Di Wu, Wei Zhu, Bin Deng, Fuhui Zhou, Jiangzhou Wang
https://arxiv.org/abs/2506.23203

Multi-Branch DNN and CRLB-Ratio-Weight Fusion for Enhanced DOA Sensing via a Massive H$^2$AD MIMO Receiver
As a green MIMO structure, massive H$^2$AD is viewed as a potential technology for the future 6G wireless network. For such a structure, it is a challenging task to design a low-complexity and high-performance fusion of target direction values sensed by different sub-array groups with fewer use of prior knowledge. To address this issue, a lightweight Cramer-Rao lower bound (CRLB)-ratio-weight fusion (WF) method is proposed, which approximates inverse CRLB of each subarray using antenna number r…

Orange U Glad - jazz Americana fusion
#flute #mandolin
https://muz4now.com/2021/orange-u-glad…

Orange U Glad - jazz Americana fusion #flute #mandolin
Stan Stewart - @muz4now

Na endlich!
https://www.dnn.de/lokales/dresden/verkehrsverbuende-vvo-und-zvon-fusion-bis-jahresende-gemeinsamer-tarif-KEKO4DTGO5GBFK5PZO2JI6HGHM.html

Ein Verkehrsverbund für Ostsachsen: VVO und ZVON streben Fusion bis Jahresende an
Der Zweckverband Oberlausitz-Niederschlesien hat den Weg für einen Zusammenschluss mit dem Verkehrsverbund Oberelbe freigemacht. So könnte endlich auch ein einheitliches Tarifsystem für Bus und Bahn in ganz Ostsachsen entstehen.

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS
Hai Ling, Tianchi Wang, Xiaohao Liu, Zhulin Tao, Lifang Yang, Xianglin Huang
https://arxiv.org/abs/2507.22880

AUV-Fusion: Cross-Modal Adversarial Fusion of User Interactions and Visual Perturbations Against VARS
Modern Visual-Aware Recommender Systems (VARS) exploit the integration of user interaction data and visual features to deliver personalized recommendations with high precision. However, their robustness against adversarial attacks remains largely underexplored, posing significant risks to system reliability and security. Existing attack strategies suffer from notable limitations: shilling attacks are costly and detectable, and visual-only perturbations often fail to align with user preferences.…

Multimodal Late Fusion Model for Problem-Solving Strategy Classification in a Machine Learning Game
Clemens Witt, Thiemo Leonhardt, Nadine Bergner, Mareen Grillenberger
https://arxiv.org/abs/2507.22426

Multimodal Late Fusion Model for Problem-Solving Strategy Classification in a Machine Learning Game
Machine learning models are widely used to support stealth assessment in digital learning environments. Existing approaches typically rely on abstracted gameplay log data, which may overlook subtle behavioral cues linked to learners' cognitive strategies. This paper proposes a multimodal late fusion model that integrates screencast-based visual data and structured in-game action sequences to classify students' problem-solving strategies. In a pilot study with secondary school students (N=149) p…

MCFuser: High-Performance and Rapid Fusion of Memory-Bound Compute-Intensive Operators
Zheng Zhang, Donglin Yang, Xiaobo Zhou, Dazhao Cheng
https://arxiv.org/abs/2506.22169

MCFuser: High-Performance and Rapid Fusion of Memory-Bound Compute-Intensive Operators
Operator fusion, a key technique to improve data locality and alleviate GPU memory bandwidth pressure, often fails to extend to the fusion of multiple compute-intensive operators due to saturated computation throughput. However, the dynamicity of tensor dimension sizes could potentially lead to these operators becoming memory-bound, necessitating the generation of fused kernels, a task hindered by limited search spaces for fusion strategies, redundant memory access, and prolonged tuning time, l…

Antisemitismuskritische Arbeit - auf der Fusion leider unerwünscht.
Quelle:
#antisemitismus

Fusionistas against Antisemitism & Antizionism on Instagram: "Der Kulturkosmos (Kuko) hat unseren antifaschistischen Infostand von Fusionistas against Antisemitism & Antizionism gestern Abend kurzfristig und unter fadenscheinigen Gründen verboten. Wir hätten angeblich Formalitäten nicht eingehalten. Dies ist eine weitere Eskalation seitens des Kuko, nachdem sie bereits in ihrem Newsletter im letzten November die antisemitischen Vorfälle auf der Fusion 2024 geleugnet haben und alle Versuche unserseits, mit ihnen in einen konstruktiven Austausch zu kommen, ignoriert haben. Antisemitismus auf der Fusion wird nicht weniger, indem man ihn ignoriert oder versucht antisemitismuskritische Arbeit zu verhindern und damit einen öffentlichen Diskurs über die Problematik zu vermeiden. Ein weiterer Ort des Austauschs und der Diskussion wird so verhindert. Ein derartiges autoritäres Verhalten widerspricht allen Ansprüchen an eine pluralistische und möglichst hierarchiefreie linke Bewegung und erschwert den gemeinsamen Kampf gegen Antisemitismus und Rassismus. Fusionistas against Antisemitism and Antizionism, 25.06.25 Link zu diesem und allen unsern vorherigen Statements im linktree/bio"
379 likes, 3 comments - fusionistasgegenantisemitismus on June 25, 2025: "Der Kulturkosmos (Kuko) hat unseren antifaschistischen Infostand von Fusionistas against Antisemitism & Antizionism gestern Abend kurzfristig und unter fadenscheinigen Gründen verboten. Wir hätten angeblich Formalitäten nicht eingehalten. Dies ist eine weitere Eskalation seitens des Kuko, nachdem sie bereits in ihrem Newsletter im letzten November die antisemitischen Vorfälle auf der Fusion 2024 geleugnet haben und al…

Weak Hopf tube algebra for domain walls between 2d gapped phases of Turaev-Viro TQFTs
Zhian Jia, Sheng Tan
https://arxiv.org/abs/2507.01515 https://…

Weak Hopf tube algebra for domain walls between 2d gapped phases of Turaev-Viro TQFTs
We investigate domain walls between 2d gapped phases of Turaev-Viro type topological quantum field theories (TQFTs) by constructing domain wall tube algebras. We begin by analyzing the domain wall tube algebra associated with bimodule categories, and then extend the construction to multimodule categories over $N$ base fusion categories. We prove that the resulting tube algebra is naturally equipped with a $C^*$ weak Hopf algebra structure. We show that topological excitations localized on domai…

@… #Cleantech 400 Mio € hat #Marvel #Fusion – und es reicht nicht. Da fehlen noch ein paar M…

400 Mio € hat Marvel Fusion – und es reicht nicht
Marvel Fusion sichert sich 400 Mio € für Fusionsreaktor-Prototyp – doch für den Durchbruch fehlen noch Milliarden.

Large condensation in enriched $\infty$-categories
Devon Stockall
https://arxiv.org/abs/2506.23632 https://arxiv.org/pdf/2506.23632…

Large condensation in enriched $\infty$-categories
Using the language of enriched $\infty$-categories, we formalize and generalize the definition of fusion n-category, and an analogue of iterative condensation of $E_i$-algebras. The former was introduced by Johnson-Freyd, and the latter by Kong, Zhang, Zhao, and Zheng. This extends categorical condensation beyond fusion n-categories to all enriched monoidal $\infty$-categories with certain colimits. The resulting theory is capable of treating symmetries of arbitrary dimension and codimension th…

Virginia county says April ransomware attack exposed employee SSNs https://therecord.media/virginia-county-says-ransomware-attack-exposed-ssns

Paramount : Wie es nach der Fusion mit Skydance Media weitergeht
Dank der Fusion mit der Produktionsgesellschaft Skydance ist Paramount Global vorerst gerettet. Doch der hauseigene Streamingdienst muss attraktiver werden.

Simulation study of neutral tungsten emissions for fusion applications
Ritu Dey, Ayushi Agrawal, Reetesh Kumar Gangwar, Deepti Sharma, Rajesh Srivastava, Malay B. Chowdhuri, Joydeep Ghosh
https://arxiv.org/abs/2509.00878

Simulation study of neutral tungsten emissions for fusion applications
The article reports electron-impact excitation cross-sections and rate coefficients for neutral tungsten for three transitions (400.87 nm, 429.46 nm, and 430.21 nm) using the relativistic distorted wave approach within the flexible atomic code. Some of these lines are also observed in tokamak plasma. Cross-sections are computed for incident electron energy up to 30 keV. The energy levels in flexible atomic code were corrected to match the NIST database. The electron impact excitation rate coeff…

Intrinsic Heralding and Optimal Decoders for Non-Abelian Topological Order
Dian Jing, Pablo Sala, Liang Jiang, Ruben Verresen
https://arxiv.org/abs/2507.23765 https://

Intrinsic Heralding and Optimal Decoders for Non-Abelian Topological Order
Topological order (TO) provides a natural platform for storing and manipulating quantum information. However, its stability to noise has only been systematically understood for Abelian TOs. In this work, we exploit the non-deterministic fusion of non-Abelian anyons to inform active error correction and design decoders where the fusion products, instead of flag qubits, herald the noise. This intrinsic heralding enhances thresholds over those of Abelian counterparts when noise is dominated by a s…

Commonwealth, which wants to build a fusion power plant, raised $863M from Nvidia's NVentures, Khosla Ventures, and Google, bringing its total raised to ~$3B (Will Wade/Bloomberg)
https://www.bloomberg.com/news/articles/202…

Is External Information Useful for Data Fusion? An Evaluation before Acquisition
Guorong Dai, Lingxuan Shao, Jinbo Chen
https://arxiv.org/abs/2507.22351 https://

Is External Information Useful for Data Fusion? An Evaluation before Acquisition
We consider a general statistical estimation problem involving a finite-dimensional target parameter vector. Beyond an internal data set drawn from the population distribution, external information, such as additional individual data or summary statistics, can potentially improve the estimation when incorporated via appropriate data fusion techniques. However, since acquiring external information often incurs costs, it is desirable to assess its utility beforehand using only the internal data. …

This years #fusion industry association reports are out; 5 of the member companies expect to ''operate a commercially viable pilot plant' by 2030, another 35 expect to be able to do it by 2035, with slightly lower numbers for that being 'deliver power to the grid' - 'commercial viability' seems to skew a little later; but still, Fusion only being *10* years away is pro…

Fusion Industry Reports - Fusion Industry Association
NEWS Fusion Industry Reports Download our 2025 Global Fusion Industry Report Download our 2025 Fusion Industry Supply Chain Report

AFUNet: Cross-Iterative Alignment-Fusion Synergy for HDR Reconstruction via Deep Unfolding Paradigm
Xinyue Li, Zhangkai Ni, Wenhan Yang
https://arxiv.org/abs/2506.23537

AFUNet: Cross-Iterative Alignment-Fusion Synergy for HDR Reconstruction via Deep Unfolding Paradigm
Existing learning-based methods effectively reconstruct HDR images from multi-exposure LDR inputs with extended dynamic range and improved detail, but they rely more on empirical design rather than theoretical foundation, which can impact their reliability. To address these limitations, we propose the cross-iterative Alignment and Fusion deep Unfolding Network (AFUNet), where HDR reconstruction is systematically decoupled into two interleaved subtasks -- alignment and fusion -- optimized throug…

Crosslisted article(s) found for physics.ao-ph. https://arxiv.org/list/physics.ao-ph/new
[1/1]:
- Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers
Giacomo Acciarini, et al.

LatentEdit: Adaptive Latent Control for Consistent Semantic Editing
Siyi Liu, Weiming Chen, Yushun Tang, Zhihai He
https://arxiv.org/abs/2509.00541 https://

LatentEdit: Adaptive Latent Control for Consistent Semantic Editing
Diffusion-based Image Editing has achieved significant success in recent years. However, it remains challenging to achieve high-quality image editing while maintaining the background similarity without sacrificing speed or memory efficiency. In this work, we introduce LatentEdit, an adaptive latent fusion framework that dynamically combines the current latent code with a reference latent code inverted from the source image. By selectively preserving source features in high-similarity, semantica…

Plasmonic Metasurfaces with Structural Chirality and Pseudo-Chirality for Enhanced Circular Dichroism and Enantiomeric Recognition
Giovanna Palermo, Bryan Guilcapi, Radoslaw Kolkowski, Alexa Guglielmelli, Dante M. Aceti, Liliana Valente, Joseph Zyss, Lucia Petti, Giuseppe Strangi
https://arxiv.org/abs/2508.00730

Plasmonic Metasurfaces with Structural Chirality and Pseudo-Chirality for Enhanced Circular Dichroism and Enantiomeric Recognition
We present the design and optical characterization of a plasmonic metasurface engineered to exhibit strong polarization anisotropy under both linearly and circularly polarized light. The metasurface consists of geometrically asymmetric gold nanostructures arranged periodically on a glass substrate. Each nanostructure is formed by the fusion of three equilateral triangles. The nanostructures simultaneously break mirror and inversion symmetries, resulting in chiral and pseudo-chiral optical respo…

Like fusion and flying cars, quantitative #DnD encounter balance is always 40 years in the future. #ttrpg https://mstdn.social/@peterdra…

Suitability of ReaxFF potential for MD modelling of lithium across low and high temperatures
Predrag S. Krstic, Swarit Dwivedi, Adri C. T. van Duin, Bruce E. Koel
https://arxiv.org/abs/2509.00807

Suitability of ReaxFF potential for MD modelling of lithium across low and high temperatures
Modeling lithium's atomic-scale behavior is critical for its roles in plasma-facing fusion components and lithium-ion batteries, yet it remains challenging across phase regimes. This study benchmarks ReaxFF, 2NN-MEAM, and SNAP potentials from 100 to 1000 K using molecular dynamics, with ensemble and cooling protocols carefully controlled. Compared to reliable experimental data, ReaxFF diverges above 800 K, underestimating density by ~10% at 1000 K and overestimating diffusivity, yielding anomal…

Particle swarm optimization of divertor targets for heat load control
H. Frerichs
https://arxiv.org/abs/2509.00206 https://arxiv.org/pdf/2509.00206

Particle swarm optimization of divertor targets for heat load control
Divertor targets in magnetic confinement fusion devices must be designed to handle extreme heat loads. Fast approximation of heat loads with FLARE based on field line reconstruction from an unstructured flux tube mesh is utilized in particle swarm optimization (PSO) of the divertor target geometry. Optimization of the outer divertor target in ITER is evaluated with a constraint for the head loads onto baffles. The optimal configuration is found to depend on assumptions for the background plasma…

According to my napkin estimations, and also assuming (unreasonably) that we will have cracked 100% fusion efficiency of E=mc² within the next few weeks, humans will have burned up the entire mantle of the Earth in approximately 2200 years.
This is using the 2023 figures for present use (15000 Mtoe, ie about 7 tonnes annually) and its 2.2% growth rate which, while suddenly up from the long standing 1.5%, is largely pre-LLMs.

Fusion power startup Commonwealth Fusion Systems raises $863M with help from Nvidia, Google, and Bill Gates, advancing clean energy technology. #climatechange #climatesolutions #climate

Nvidia, Google, and Bill Gates help Commonwealth Fusion Systems raise $863M | TechCrunch
Commonwealth Fusion Systems has raised nearly $3 billion to commercialize its fusion power plant. It hopes to send electricity to the grid in the early 2030s.

Unlocking the Effectiveness of LoRA-FP for Seamless Transfer Implantation of Fingerprints in Downstream Models
Zhenhua Xu, Zhaokun Yan, Binhan Xu, Xin Tong, Haitao Xu, Yourong Chen, Meng Han
https://arxiv.org/abs/2509.00820

Unlocking the Effectiveness of LoRA-FP for Seamless Transfer Implantation of Fingerprints in Downstream Models
With the rapid advancement of large language models (LLMs), safeguarding intellectual property (IP) has become increasingly critical. To address the challenges of high costs and potential contamination in fingerprint integration, we propose LoRA-FP, a lightweight, plug-and-play framework that embeds backdoor fingerprints into LoRA adapters through constrained fine-tuning. This design enables seamless fingerprint transplantation via parameter fusion, eliminating the need for full-parameter updat…

Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics
Hsin-Hsiung Huang, Hayden Hampton
https://arxiv.org/abs/2506.20935

Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics
Forecasting geopolitical conflict from data sources like the Global Database of Events, Language, and Tone (GDELT) is a critical challenge for national security. The inherent sparsity, burstiness, and overdispersion of such data cause standard deep learning models, including the Temporal Fusion Transformer (TFT), to produce unreliable long-horizon predictions. We introduce STFT-VNNGP, a hybrid architecture that won the 2023 Algorithms for Threat Detection (ATD) competition by overcoming these l…

Machine Learning Based Efficiency Calculator (MaLBEC) for Nuclear Fusion Diagnostics
Kimberley Lennon, Chantal Shand, Gemma Wilson, Robin Smith
https://arxiv.org/abs/2507.19425 …

Machine Learning Based Efficiency Calculator (MaLBEC) for Nuclear Fusion Diagnostics
Diagnostics are critical for commercial and research fusion machines, since measuring and understanding plasma features is important to sustaining fusion reactions. The neutron flux (and therefore fusion power) can be indirectly calculated using neutron activation analyses, where potentially large numbers of activation foils are placed in the neutron flux, and delayed gammas from key reactions are measured via gamma spectrometry. In gamma spectrometry, absolute efficiency forms part of the acti…

Ultrashort Time-Integrated Diagnosis of Laser-Heated Deuterium Ions in Dense Plasma via Fusion Neutron Spectra
Jie Feng, Hao Xu, Mingxuan Wei, Mingyang Zhu, Xichen Hu, Bingzhan Shi, Fuyuan Wu, Weijun Zhou, Wenchao Yan, Guoqiang Zhang, Jinguang Wang, Yifei Li, Xin Lu, Liming Chen
https://arxiv.org/abs/2509.00659

Ultrashort Time-Integrated Diagnosis of Laser-Heated Deuterium Ions in Dense Plasma via Fusion Neutron Spectra
The ultrashort time-integrated diagnosis of ions plays a vital role in high energy density physics research. However, it is extremely challenging to measure in experiment. Here, we demonstrate a reliable approach for investigating the dynamics of deuterium ions in dense plasma. By irradiating a heavy water stream with the hundred Hertz repetitive intense femtosecond laser pulses, the neutrons from D(D,n)3He reaction can be detected via a single Time-of-Flight detector to accumulate the spectrum…

Lighting the Way for BRIGHT: Reproducible Baselines with Anserini, Pyserini, and RankLLM
Yijun Ge, Sahel Sharifymoghaddam, Jimmy Lin
https://arxiv.org/abs/2509.02558 https://

Lighting the Way for BRIGHT: Reproducible Baselines with Anserini, Pyserini, and RankLLM
The BRIGHT benchmark is a dataset consisting of reasoning-intensive queries over diverse domains. We explore retrieval results on BRIGHT using a range of retrieval techniques, including sparse, dense, and fusion methods, and establish reproducible baselines. We then apply listwise reranking with large language models (LLMs) to further investigate the impact of reranking on reasoning-intensive queries. These baselines are integrated into popular retrieval and reranking toolkits Anserini, Pyserin…

Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection
Yassine El Kheir, Arnab Das, Enes Erdem Erdogan, Fabian Ritter-Guttierez, Tim Polzehl, Sebastian M\"oller
https://arxiv.org/abs/2507.20417

Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection
Recent advances in synthetic speech have made audio deepfakes increasingly realistic, posing significant security risks. Existing detection methods that rely on a single modality, either raw waveform embeddings or spectral based features, are vulnerable to non spoof disturbances and often overfit to known forgery algorithms, resulting in poor generalization to unseen attacks. To address these shortcomings, we investigate hybrid fusion frameworks that integrate self supervised learning (SSL) bas…

Conservative fusion of unbiased partial state estimates: CI is optimal
Jochen Trumpf, Behzad Zamani, Chris Manzie
https://arxiv.org/abs/2507.16216 https://…

Conservative fusion of unbiased partial state estimates: CI is optimal
We show that Covariance Intersection (CI) is optimal amongst all conservative unbiased linear fusion rules also in the general case of information fusion of two unbiased partial state estimates, significantly generalizing the known optimality result for fusion of full state estimates. In fact, we prove the much stronger result that three different optimization problems are equivalent, namely the abstract optimal conservative unbiased linear information fusion problem with respect to a strictly …

Gauging Non-Invertible Symmetries in (2 1)d Topological Orders
Mahesh K. N. Balasubramanian, Matthew Buican, Clement Delcamp, Rajath Radhakrishnan
https://arxiv.org/abs/2507.01142

Gauging Non-Invertible Symmetries in (2+1)d Topological Orders
We present practical and formal methods for gauging non-invertible symmetries in (2+1)d topological quantum field theories. Along the way, we generalize various aspects of invertible 0-form gauging, including symmetry fractionalization, discrete torsion, and the fixed point theorem for symmetry action on lines. Our approach involves two complementary strands: the fusion of topological interfaces and Morita theory of fusion 2-categories. We use these methods to derive constraints on gaugeable sy…

A Multi-Criteria Evaluation Framework for Siting Fusion Energy Facilities: Application and Evaluation of U.S. Coal Power Plants
Muhammad R. Abdussami, Kevin Daley, Gabrielle Hoelzle, Aditi Verma
https://arxiv.org/abs/2506.22489

A Multi-Criteria Evaluation Framework for Siting Fusion Energy Facilities: Application and Evaluation of U.S. Coal Power Plants
This paper proposes a comprehensive methodology for siting fusion energy facilities, integrating expert judgment, geospatial data, and multi-criteria decision making tools to evaluate site suitability systematically. As a case study, we apply this framework to all currently operational coal power plant sites in the United States to examine their potential for hosting future fusion facilities at a time when these coal plants are shut down on reaching their end of life - timelines which are expec…

A Multimodal Cross-View Model for Predicting Postoperative Neck Pain in Cervical Spondylosis Patients
Jingyang Shan, Qishuai Yu, Jiacen Liu, Shaolin Zhang, Wen Shen, Yanxiao Zhao, Tianyi Wang, Xiaolin Qin, Yiheng Yin
https://arxiv.org/abs/2509.02256

A Multimodal Cross-View Model for Predicting Postoperative Neck Pain in Cervical Spondylosis Patients
Neck pain is the primary symptom of cervical spondylosis, yet its underlying mechanisms remain unclear, leading to uncertain treatment outcomes. To address the challenges of multimodal feature fusion caused by imaging differences and spatial mismatches, this paper proposes an Adaptive Bidirectional Pyramid Difference Convolution (ABPDC) module that facilitates multimodal integration by exploiting the advantages of difference convolution in texture extraction and grayscale invariance, and a Feat…

Estimation of Phylogenetic Tree using Gene Sequencing Data
S M Rafiuddin
https://arxiv.org/abs/2509.01407 https://arxiv.org/pdf/2509.01407

Estimation of Phylogenetic Tree using Gene Sequencing Data
A phylogenetic tree is an important way in Bioinformatics to find the evolutionary relationship among biological species. In this research, a proposed model is described for the estimation of a phylogenetic tree for a given set of data. To estimate a phylogenetic tree there are certain necessary steps have to be considered. Gene sequences are useful data resources to estimate the relationship among species at the molecular level. In this research, the approach is to create a fusion between the …

Polarized tau decay and CP violation in ultraperipheral heavy-ion collisions
Amaresh Jaiswal
https://arxiv.org/abs/2509.02228 https://arxiv.org/pdf/2509.02…

Polarized tau decay and CP violation in ultraperipheral heavy-ion collisions
We investigate the role of $τ$-lepton polarization in ultraperipheral heavy-ion collisions (UPCs) as a novel application of the intense electromagnetic fields generated in such processes. In particular, we analyze the decay distributions of polarized $τ$-leptons produced via photon-photon fusion, focusing on both leptonic and semi-leptonic channels. We show that the external magnetic field present in UPCs induces a preferred spin quantization axis, which modifies the angular and energy distri…

On the influence of powder particle size on single-track formation in laser powder bed fusion of AlSi10Mg alloy
Y. Solyaev, V. Dobryanskiy, Nguyen Long, Stanislav Chernyshikhin
https://arxiv.org/abs/2507.23422

On the influence of powder particle size on single-track formation in laser powder bed fusion of AlSi10Mg alloy
In this paper, we present the results of single-track experiments conducted for different fractions of standard AlSi10Mg powder, which were sieved to achieve varying mean size of the particles. We observed strong differences in the melting behaviour of fractions at relatively low levels of input energy in laser powder bed fusion (LPBF) process. Namely, the remarkable particle size effect arises for the position of lack of fusion boundary, i.e. for the range of process parameters where the laser…

Development of an Atomic Layer Deposition System for Deposition of Alumina as a Hydrogen Permeation Barrier
Zachary R. Robinson, Jeffrey Woodward, Alexander C. Kozen, Joshua Ruby, Tyler Liao, Luke Herter, Rashad Ahmadov, Mark D. Wittman, Matthew Sharpe
https://arxiv.org/abs/2507.00958

Development of an Atomic Layer Deposition System for Deposition of Alumina as a Hydrogen Permeation Barrier
Tritium permeation into and through materials poses a critical challenge for the development of nuclear fusion reactors. Minimizing tritium permeation is essential for the safe and efficient use of available fuel supplies. In this work, we present the design, construction, and validation of custom atomic layer deposition (ALD) and deuterium permeation measurement systems aimed at developing thin-film hydrogen permeation barriers. Using the ALD system, we deposited conformal Al2O3 films on coppe…

In Lippstadt wurden das evangelische Krankenhaus und das katholische Krankenhaus zum christlichen Krankenhaus fusioniert.
Das Problem: Der katholische Träger lässt keine medizinisch indizierten Abtreibungen zu. Der Chefarzt des evangelischem Krankenhauses hat im Arbeitsvertrag festgeschrieben, dass er medizinisch indizierte Abtreibungen durchführen darf.
M.E. hätte der katholische Betreiber der Fusion nicht zustimmen dürfen wegen des Arbeitsvertrages. Der evangelische Betreiber hätte…

In Lippstadt wurden das evangelische Krankenhaus und das katholische Krankenhaus zum christlichen Krankenhaus fusioniert.
Das Problem: Der katholische Träger lässt keine medizinisch indizierten Abtreibungen zu. Der Chefarzt des evangelischem Krankenhauses hat im Arbeitsvertrag festgeschrieben, dass er medizinisch indizierte Abtreibungen durchführen darf.
M.E. hätte der katholische Betreiber der Fusion nicht zustimmen dürfen wegen des Arbeitsvertrages. Der evangelische Betreiber hätte…

Researchers Solve 35-Year-Old Fusion Mystery With Bench-Top Reactor
https://gizmodo.com/researchers-solve-35-year-old-fusion-mystery-with-bench-top-reactor-2000645186

Applications of the factorization theorem of conformal blocks to vertex operator algebras
Xu Gao, Jianqi Liu
https://arxiv.org/abs/2508.01294 https://arxiv…

Applications of the factorization theorem of conformal blocks to vertex operator algebras
We apply the factorization and vector bundle propositionerty of the sheaves of conformal blocks on $\overline{\mathscr{M}}_{g,n}$. defined by vertex operator algebras (VOAs) and give geometric proofs of essential results in the representation theory of strongly rational VOAs. We first prove the associativity of the fusion tensor product by investigating four-point conformal blocks on genus zero curves. Then we give a formula to calculate the ranks of VOA-conformal block bundles. Finally, by inv…

QuickSilver -- Speeding up LLM Inference through Dynamic Token Halting, KV Skipping, Contextual Token Fusion, and Adaptive Matryoshka Quantization
Danush Khanna, Aditya Kumar Guru, Srivarshinee Sridhar, Zidan Ahmed, Rubhav Bahirwani, Meetu Malhotra, Vinija Jain, Aman Chadha, Amitava Das, Kripabandhu Ghosh
https://arxiv.org/abs/2…

QuickSilver -- Speeding up LLM Inference through Dynamic Token Halting, KV Skipping, Contextual Token Fusion, and Adaptive Matryoshka Quantization
Inference accounts for the majority of latency and energy consumption in large language model (LLM) deployments, often exceeding 90% of total cost. While training-time efficiency has seen extensive progress, runtime optimization remains a key bottleneck, particularly under autoregressive decoding. Existing approaches -- such as pruning, quantization, early exits, and speculative decoding -- often require retraining, architectural changes, or disrupt decoding compatibility. We introduce QuickSil…

A combined Machine Learning and Finite Element Modelling tool for the surgical planning of craniosynostosis correction
Itxasne Ant\'unez S\'aenz, Ane Alberdi Aramendi, David Dunaway, Juling Ong, Lara Deli\`ege, Amparo S\'aenz, Anita Ahmadi Birjandi, Noor UI Owase Jeelani, Silvia Schievano, Alessandro Borghi
https://a…

A combined Machine Learning and Finite Element Modelling tool for the surgical planning of craniosynostosis correction
Craniosynostosis is a medical condition that affects the growth of babies' heads, caused by an early fusion of cranial sutures. In recent decades, surgical treatments for craniosynostosis have significantly improved, leading to reduced invasiveness, faster recovery, and less blood loss. At Great Ormond Street Hospital (GOSH), the main surgical treatment for patients diagnosed with sagittal craniosynostosis (SC) is spring assisted cranioplasty (SAC). This procedure involves a 15x15 mm2 osteotomy…

Orange U Glad - jazz Americana fusion
#flute #mandolin
https://muz4now.com/2021/orange-u-glad…

Orange U Glad - jazz Americana fusion #flute #mandolin
Stan Stewart - @muz4now

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…

Searching for Dark Pions with the MoEDAL-MAPP Detector at the LHC
Shafakat Arifeen, Pierre-Philippe Ouimet, James Pinfold, Michael Staelens
https://arxiv.org/abs/2509.02821 http…

Searching for Dark Pions with the MoEDAL-MAPP Detector at the LHC
We investigate the potential for detecting pion-like dark matter within the framework of a Strongly Interacting Massive Particle (SIMP) model using the MoEDAL Apparatus for Penetrating Particles (MAPP) at the LHC. The model, motivated by Chiral Perturbation Theory, features milli-charged dark pions that couple to Standard Model particles via kinetic mixing with a dark photon. Production channels considered include Drell--Yan pair production and photon fusion via the Wess--Zumino--Witten term, t…

MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusion
Zihan Wang, Jeff Tan, Tarasha Khurana, Neehar Peri, Deva Ramanan
https://arxiv.org/abs/2507.23782 https://

MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusion
We address the problem of dynamic scene reconstruction from sparse-view videos. Prior work often requires dense multi-view captures with hundreds of calibrated cameras (e.g. Panoptic Studio). Such multi-view setups are prohibitively expensive to build and cannot capture diverse scenes in-the-wild. In contrast, we aim to reconstruct dynamic human behaviors, such as repairing a bike or dancing, from a small set of sparse-view cameras with complete scene coverage (e.g. four equidistant inward-faci…

Choice Outweighs Effort: Facilitating Complementary Knowledge Fusion in Federated Learning via Re-calibration and Merit-discrimination
Ming Yang, Dongrun Li, Xin Wang, Xiaoyang Yu, Xiaoming Wu, Shibo He
https://arxiv.org/abs/2508.17954

Choice Outweighs Effort: Facilitating Complementary Knowledge Fusion in Federated Learning via Re-calibration and Merit-discrimination
Cross-client data heterogeneity in federated learning induces biases that impede unbiased consensus condensation and the complementary fusion of generalization- and personalization-oriented knowledge. While existing approaches mitigate heterogeneity through model decoupling and representation center loss, they often rely on static and restricted metrics to evaluate local knowledge and adopt global alignment too rigidly, leading to consensus distortion and diminished model adaptability. To addre…

Automated discovery of heralded ballistic graph state generators for fusion-based photonic quantum computation
Gavin S. Hartnett, Dave Kielpinski, Smarak Maity, Pranav S. Mundada, Yuval Baum, Michael R. Hush
https://arxiv.org/abs/2508.16505

Automated discovery of heralded ballistic graph state generators for fusion-based photonic quantum computation
Designing photonic circuits that prepare graph states with high fidelity and success probability is a central challenge in linear optical quantum computing. Existing approaches rely on hand-crafted designs or fusion-based assemblies. In the absence of multiplexing/boosting, both post-selected ballistic circuits and sequential fusion builds exhibit exponentially decreasing single-shot yields, motivating automated discovery of higher-success circuits. We present a general-purpose optimization fra…

MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction
Andrew Broad, Jason Keighley, Lucy Godson, Alex Wright
https://arxiv.org/abs/2509.02598 http…

MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction
We present a novel approach which extends the existing Fully Convolutional One-Stage Object Detector (FCOS) for mitotic figure detection. Our composite model adds a Feedback Attention Ladder CNN (FAL-CNN) model for classification of normal versus abnormal mitotic figures, feeding into a fusion network that is trained to generate adjustments to bounding boxes predicted by FCOS. Our network aims to reduce the false positive rate of the FCOS object detector, to improve the accuracy of object detec…

HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar, Swarup Ranjan Behera, Pailla Balakrishna Reddy, Arun Balaji Buduru, Rajesh Sharma
https://arxiv.org/abs/2506.03403

HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition
Compression-based representations (CBRs) from neural audio codecs such as EnCodec capture intricate acoustic features like pitch and timbre, while representation-learning-based representations (RLRs) from pre-trained models trained for speech representation learning such as WavLM encode high-level semantic and prosodic information. Previous research on Speech Emotion Recognition (SER) has explored both, however, fusion of CBRs and RLRs haven't been explored yet. In this study, we solve this gap…

Homomorphism, substructure and ideal: Elementary but rigorous aspects of renormalization group or hierarchical structure of topological orders
Yoshiki Fukusumi, Yuma Furuta
https://arxiv.org/abs/2506.23155

Homomorphism, substructure and ideal: Elementary but rigorous aspects of renormalization group or hierarchical structure of topological orders
We study ring homomorphisms between fusion rings appearing in conformal field theories connected under massless renormalization group (RG) flows. By interpreting the elementary relationship between homomorphism, quotient ring, and projection, we propose a general quantum Hamiltonian formalism of a massless and massive RG flow with an emphasis on generalized symmetry. In our formalism, the noninvertible nature of the ideal of a fusion ring plays a fundamental role as a condensation rule between …

Satellitenbetreiber SES fusioniert mit Intelsat
Durch die Fusion steigt SES zum größten Betreiber geostationärer Satelliten im Europäischen Wirtschaftsraum auf und soll die Unabhängigkeit der EU verbessern.
https://www.

ClusterFusion: Expanding Operator Fusion Scope for LLM Inference via Cluster-Level Collective Primitive
Xinhao Luo, Zihan Liu, Yangjie Zhou, Shihan Fang, Ziyu Huang, Yu Feng, Chen Zhang, Shixuan Sun, Zhenzhe Zheng, Jingwen Leng, Minyi Guo
https://arxiv.org/abs/2508.18850

ClusterFusion: Expanding Operator Fusion Scope for LLM Inference via Cluster-Level Collective Primitive
Large language model (LLM) decoding suffers from high latency due to fragmented execution across operators and heavy reliance on off-chip memory for data exchange and reduction. This execution model limits opportunities for fusion and incurs significant memory traffic and kernel launch overhead. While modern architectures such as NVIDIA Hopper provide distributed shared memory and low-latency intra-cluster interconnects, they expose only low-level data movement instructions, lacking structured …

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Supawich Sitdhipol, Waritwong Sukprasongdee, Ekapol Chuangsuwanich, Rina Tse
https://arxiv.org/abs/2507.19947

Spatial Language Likelihood Grounding Network for Bayesian Fusion of Human-Robot Observations
Fusing information from human observations can help robots overcome sensing limitations in collaborative tasks. However, an uncertainty-aware fusion framework requires a grounded likelihood representing the uncertainty of human inputs. This paper presents a Feature Pyramid Likelihood Grounding Network (FP-LGN) that grounds spatial language by learning relevant map image features and their relationships with spatial relation semantics. The model is trained as a probability estimator to capture a…

Sync-TVA: A Graph-Attention Framework for Multimodal Emotion Recognition with Cross-Modal Fusion
Zeyu Deng, Yanhui Lu, Jiashu Liao, Shuang Wu, Chongfeng Wei
https://arxiv.org/abs/2507.21395

Sync-TVA: A Graph-Attention Framework for Multimodal Emotion Recognition with Cross-Modal Fusion
Multimodal emotion recognition (MER) is crucial for enabling emotionally intelligent systems that perceive and respond to human emotions. However, existing methods suffer from limited cross-modal interaction and imbalanced contributions across modalities. To address these issues, we propose Sync-TVA, an end-to-end graph-attention framework featuring modality-specific dynamic enhancement and structured cross-modal fusion. Our design incorporates a dynamic enhancement module for each modality and…

Athens-based defense tech startup Delian Alliance Industries, which makes its own hardware, software, and sensor fusion systems, raised a $14M Series A (Financial Times)
https://www.ft.com/content/9edc099b-509c-4640-8eb8-d28a80e7c882

Higgs production via vector-boson fusion at the LHC
Gaetano Barone, Jiayi Chen, Stephane Cooperstein, Nikita Dolganov, Silvia Ferrario Ravasio, Yacine Haddad, Stefan H\"oche, Barbara J\"ager, Alexander Karlberg, Alexander M\"uck, Mathieu Pellen, Christian T. Preuss, Daniel Reichelt, Simon Reinhardt, Marco Zaro
https://arxiv.…

Higgs production via vector-boson fusion at the LHC
In this article, we summarise the recent experimental measurements and theoretical work on Higgs boson production via vector-boson fusion at the LHC. Along with this, we provide state-of-the-art predictions at fixed order as well as with parton-shower corrections within the Standard Model at 13.6 TeV. The results are presented in the form of multi-differential distributions as well as in the Simplified Template Cross Section bins. All materials and outputs of this study are available on public …

The properties of resistive MHD modes and unstable spectra in advanced tokamak regimes
M. Coste-Sarguet, J. P. Graves
https://arxiv.org/abs/2509.03429 https://

The properties of resistive MHD modes and unstable spectra in advanced tokamak regimes
Advanced tokamak regimes, featuring extended regions of low magnetic shear, are promising candidates for future fusion reactors but are also more prone to specific kinds of MHD instabilities. The proximity to a rational surface in a very low shear region weakens field line bending stabilisation and amplifies the effects of toroidal coupling between modes, leading to the emergence of long-wavelength resistive infernal modes. These modes can grow collectively as a discrete spectrum, leading to a …

A general fusion procedure for open $\mathfrak{gl}(N)$ spin chains: Application to the ABJM spin chain
Nan Bai
https://arxiv.org/abs/2507.19394 https://arx…

A general fusion procedure for open $\mathfrak{gl}(N)$ spin chains: Application to the ABJM spin chain
We formulate a general fusion procedure for open $\mathfrak{gl}(N)$ spin chains. We construct the fused boundary reflection matrices and the corresponding fused reflection equations. By using the intertwining relation between the fused reflection matrices and the fusion operator, we identify the invariant subspace of the fused reflection matrices carrying the irreducible representations of $\mathfrak{gl}(N)$. We also construct the fused transfer matrix and evaluate it explicitly in the total te…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/5]:
- SmartPNT-MSF: A Multi-Sensor Fusion Dataset for Positioning and Navigation Research
Feng Zhu, Zihang Zhang, Kangcheng Teng, Abduhelil Yakup, Xiaohong Zhang

MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
Peiting Tian, Xi Chen, Haixia Bi, Fan Li
https://arxiv.org/abs/2506.23700 …

MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
Medical image segmentation plays a crucial role in clinical diagnosis and treatment planning, where accurate boundary delineation is essential for precise lesion localization, organ identification, and quantitative assessment. In recent years, deep learning-based methods have significantly advanced segmentation accuracy. However, two major challenges remain. First, the performance of these methods heavily relies on large-scale annotated datasets, which are often difficult to obtain in medical s…

Review of the Higgs boson production via vector boson fusion and its decay into bottom quarks in $pp$ collisions at $\sqrt{s}=8,13$ TeV
Fikriye C I Kaya, Ibrahim Mirza
https://arxiv.org/abs/2507.22765 …

Review of the Higgs boson production via vector boson fusion and its decay into bottom quarks in $pp$ collisions at $\sqrt{s}=8,13$ TeV
We present a comprehensive overview of the vector boson fusion production and the following decay of the Higgs boson to two bottom quarks (\(H\!\to\! b\bar{b}\)), which dominates the Higgs total width yet remains experimentally challenging because of substantial QCD multijet backgrounds. We overview the use of boosted decision trees, which advance jet reconstruction and flavour tagging by including boosted topologies and deep-learning-based \(b\)-tagging and which improve sensitivity in associa…

SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather
Edoardo Palladin, Roland Dietze, Praveen Narayanan, Mario Bijelic, Felix Heide
https://arxiv.org/abs/2508.16408

SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather
Multimodal sensor fusion is an essential capability for autonomous robots, enabling object detection and decision-making in the presence of failing or uncertain inputs. While recent fusion methods excel in normal environmental conditions, these approaches fail in adverse weather, e.g., heavy fog, snow, or obstructions due to soiling. We introduce a novel multi-sensor fusion approach tailored to adverse weather conditions. In addition to fusing RGB and LiDAR sensors, which are employed in recent…

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure
Igor Sfiligoi, Emily A. Belli, Jeff Candy
https://arxiv.org/abs/2507.22245

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure
First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a un…

EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis
Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, Ghulam Rasool
https://arxiv.org/abs/2506.22446

EAGLE: Efficient Alignment of Generalized Latent Embeddings for Multimodal Survival Prediction with Interpretable Attribution Analysis
Accurate cancer survival prediction requires integration of diverse data modalities that reflect the complex interplay between imaging, clinical parameters, and textual reports. However, existing multimodal approaches suffer from simplistic fusion strategies, massive computational requirements, and lack of interpretability-critical barriers to clinical adoption. We present EAGLE (Efficient Alignment of Generalized Latent Embeddings), a novel deep learning framework that addresses these limitati…

DEFNet: Multitasks-based Deep Evidential Fusion Network for Blind Image Quality Assessment
Yiwei Lou, Yuanpeng He, Rongchao Zhang, Yongzhi Cao, Hanpin Wang, Yu Huang
https://arxiv.org/abs/2507.19418

DEFNet: Multitasks-based Deep Evidential Fusion Network for Blind Image Quality Assessment
Blind image quality assessment (BIQA) methods often incorporate auxiliary tasks to improve performance. However, existing approaches face limitations due to insufficient integration and a lack of flexible uncertainty estimation, leading to suboptimal performance. To address these challenges, we propose a multitasks-based Deep Evidential Fusion Network (DEFNet) for BIQA, which performs multitask optimization with the assistance of scene and distortion type classification tasks. To achieve a more…

SmartPNT-MSF: A Multi-Sensor Fusion Dataset for Positioning and Navigation Research
Feng Zhu, Zihang Zhang, Kangcheng Teng, Abduhelil Yakup, Xiaohong Zhang
https://arxiv.org/abs/2507.19079

SmartPNT-MSF: A Multi-Sensor Fusion Dataset for Positioning and Navigation Research
High-precision navigation and positioning systems are critical for applications in autonomous vehicles and mobile mapping, where robust and continuous localization is essential. To test and enhance the performance of algorithms, some research institutions and companies have successively constructed and publicly released datasets. However, existing datasets still suffer from limitations in sensor diversity and environmental coverage. To address these shortcomings and advance development in relat…

EIFNet: Leveraging Event-Image Fusion for Robust Semantic Segmentation
Zhijiang Li, Haoran He
https://arxiv.org/abs/2507.21971 https://arxiv.org/pdf/2507.2…

EIFNet: Leveraging Event-Image Fusion for Robust Semantic Segmentation
Event-based semantic segmentation explores the potential of event cameras, which offer high dynamic range and fine temporal resolution, to achieve robust scene understanding in challenging environments. Despite these advantages, the task remains difficult due to two main challenges: extracting reliable features from sparse and noisy event streams, and effectively fusing them with dense, semantically rich image data that differ in structure and representation. To address these issues, we propose…

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization
T. Slendebroek, A. O. Nelson, O. M. Meneghini, G. Dose, A. G. Ghiozzi, J. Harvey, B. C. Lyons, J. McClenaghan, T. F. Neiser, D. B. Weisberg, M. G. Yoo, E. Bursch, C. Holland
https://arxiv.org/abs/2507.196…

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization
The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200,000 integrated design evaluations were performed exploring the trade-offs between capital…

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments
Chenglong Qian, Yang Xu, Xiufang Shi, Jiming Chen, Liang Li
https://arxiv.org/abs/2507.18317

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments
In robotic navigation, maintaining precise pose estimation and navigation in complex and dynamic environments is crucial. However, environmental challenges such as smoke, tunnels, and adverse weather can significantly degrade the performance of single-sensor systems like LiDAR or GPS, compromising the overall stability and safety of autonomous robots. To address these challenges, we propose AF-RLIO: an adaptive fusion approach that integrates 4D millimeter-wave radar, LiDAR, inertial measuremen…

A Bayesian approach to time-domain Photonic Doppler Velocimetry
J. R. Allison (First Light Fusion Ltd), R. Bordas (First Light Fusion Ltd), J. Read (First Light Fusion Ltd), G. Burdiak (First Light Fusion Ltd), V. Beltr\'an (First Light Fusion Ltd), N. Joiner (First Light Fusion Ltd), H. Doyle (First Light Fusion Ltd), N. Hawker (First Light Fusion Ltd), J. Skidmore (First Light Fusion Ltd), T. Ao (Sandia National Laboratories), A. Porwitzky (Sandia National Laboratories), D. Dolan…

A Bayesian approach to time-domain Photonic Doppler Velocimetry
Photonic Doppler Velocimetry (PDV) is an established technique for measuring the velocities of fast-moving surfaces in high-energy-density experiments. In the standard approach to PDV analysis, a short-time Fourier transform (STFT) is used to generate a spectrogram from which the velocity history of the target is inferred. The user chooses the form, duration and separation of the window function. Here we present a Bayesian approach to infer the velocity directly from the PDV oscilloscope trace,…

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
Maximilian Tschuchnig, Michael Gadermayr, Khalifa Djemal
https://arxiv.org/abs/2507.19843

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
Automated breast cancer classification from mammography remains a significant challenge due to subtle distinctions between benign and malignant tissue. In this work, we present a hybrid framework combining deep convolutional features from a ResNet-50 backbone with handcrafted descriptors and transformer-based embeddings. Using the CBIS-DDSM dataset, we benchmark our ResNet-50 baseline (AUC: 78.1%) and demonstrate that fusing handcrafted features with deep ResNet-50 and DINOv2 features improves …

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
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- GUNNEL: Guided Mixup Augmentation and Multi-Model Fusion for Aquatic Animal Segmentation
Minh-Quan Le, Trung-Nghia Le, Tam V. Nguyen, Isao Echizen, Minh-Triet Tran

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
Muhammad Ibrahim, Naveed Akhtar, Haitian Wang, Saeed Anwar, Ajmal Mian
https://arxiv.org/abs/2507.19304

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes
Fusion of LiDAR and RGB data has the potential to enhance outdoor 3D object detection accuracy. To address real-world challenges in outdoor 3D object detection, fusion of LiDAR and RGB input has started gaining traction. However, effective integration of these modalities for precise object detection task still remains a largely open problem. To address that, we propose a MultiStream Detection (MuStD) network, that meticulously extracts task-relevant information from both data modalities. The ne…

SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
Ji Qi, Xinchang Zhang, Dingqi Ye, Yongjia Ruan, Xin Guo, Shaowen Wang, Haifeng Li
https://arxiv.org/abs/2506.20599

SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
The rapid advancement of generative artificial intelligence is producing fake remote sensing imagery (RSI) that is increasingly difficult to detect, potentially leading to erroneous intelligence, fake news, and even conspiracy theories. Existing forgery detection methods typically rely on single visual features to capture predefined artifacts, such as spatial-domain cues to detect forged objects like roads or buildings in RSI, or frequency-domain features to identify artifacts from up-sampling …