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SplatBus: A Gaussian Splatting Viewer Framework via GPU Interprocess Communication
Yinghan Xu, Th\'eo Morales, John Dingliana
https://arxiv.org/abs/2601.15431 https://arxiv.org/pdf/2601.15431 https://arxiv.org/html/2601.15431
arXiv:2601.15431v1 Announce Type: new
Abstract: Radiance field-based rendering methods have attracted significant interest from the computer vision and computer graphics communities. They enable high-fidelity rendering with complex real-world lighting effects, but at the cost of high rendering time. 3D Gaussian Splatting solves this issue with a rasterisation-based approach for real-time rendering, enabling applications such as autonomous driving, robotics, virtual reality, and extended reality. However, current 3DGS implementations are difficult to integrate into traditional mesh-based rendering pipelines, which is a common use case for interactive applications and artistic exploration. To address this limitation, this software solution uses Nvidia's interprocess communication (IPC) APIs to easily integrate into implementations and allow the results to be viewed in external clients such as Unity, Blender, Unreal Engine, and OpenGL viewers. The code is available at https://github.com/RockyXu66/splatbus.
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« Appelons un chat un chat : l’administration de Donald Trump veut faire taire quiconque dit du mal de lui Š la télévision, parce que Trump ne fait que regarder la télé »

TIL that WB0RLJ Jim posts videos of his POTA activations keyed by time, so you can find your call in his video description with a link straight to the time in the video. Very cool!
I also read his QRZ page and discovered that I did something that he dislikes. I've heard other ops say that if someone gives a partial call, you should reply with your sign twice to cut down on back-and-forth, and now I kn…

“What’s exciting is that we can now point to a specific viral component that can be redesigned. It means future adenoviral vaccines can keep all their advantages while sidestepping the rare immune misfire that causes VITT”
Scientists Finally Solve the Mystery Behind Rare COVID Vaccine Blood Clots
https://scitechdaily.com/scientists-finally-solve-the-mystery-behind-rare-covid-vaccine-blood-clots/

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/3]:
- SMaRT: Online Reusable Resource Assignment and an Application to Mediation in the Kenyan Judiciary
Farabi, Pinto, Lu, Ramos-Maqueda, Das, Deeb, Sautmann
https://arxiv.org/abs/2602.18431 https://mastoxiv.page/@arXiv_csCY_bot/116119352329590193
- Benchmarking Distilled Language Models: Performance and Efficiency in Resource-Constrained Settings
Sachin Gopal Wani, Eric Page, Ajay Dholakia, David Ellison
https://arxiv.org/abs/2602.20164 https://mastoxiv.page/@arXiv_csCL_bot/116130101399805837
- VISION-ICE: Video-based Interpretation and Spatial Identification of Arrhythmia Origins via Neura...
Dorsa EPMoghaddam, Feng Gao, Drew Bernard, Kavya Sinha, Mehdi Razavi, Behnaam Aazhang
https://arxiv.org/abs/2602.20165 https://mastoxiv.page/@arXiv_csCV_bot/116130222034322594
- Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Un...
KMA Solaiman, Joshua Sebastian, Karma Tobden
https://arxiv.org/abs/2602.20168 https://mastoxiv.page/@arXiv_csCY_bot/116130239074411770
- Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Yang, Tian, Jia, Zhang, Zheng, Wang, Su, He, Liu, Lan
https://arxiv.org/abs/2602.20176 https://mastoxiv.page/@arXiv_qbioBM_bot/116130281674122586
- Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic St...
Aniruddha Bora, Isabel K. Alvarez, Julie Chalfant, Chryssostomos Chryssostomidis
https://arxiv.org/abs/2602.20177 https://mastoxiv.page/@arXiv_csNE_bot/116130397676559696
- Data-Driven Deep MIMO Detection:Network Architectures and Generalization Analysis
Yongwei Yi, Xinping Yi, Wenjin Wang, Xiao Li, Shi Jin
https://arxiv.org/abs/2602.20178 https://mastoxiv.page/@arXiv_eessSP_bot/116130257424413457
- OrgFlow: Generative Modeling of Organic Crystal Structures from Molecular Graphs
Mohammadmahdi Vahediahmar, Matthew A. McDonald, Feng Liu
https://arxiv.org/abs/2602.20195 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/116130271189617558
- KEMP-PIP: A Feature-Fusion Based Approach for Pro-inflammatory Peptide Prediction
Soumik Deb Niloy, Md. Fahmid-Ul-Alam Juboraj, Swakkhar Shatabda
https://arxiv.org/abs/2602.20198 https://mastoxiv.page/@arXiv_qbioQM_bot/116130341315320687
- Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
Shaorong Chen, Jingbo Zhou, Jun Xia
https://arxiv.org/abs/2602.20209 https://mastoxiv.page/@arXiv_qbioQM_bot/116130374083646541
- The Sim-to-Real Gap in MRS Quantification: A Systematic Deep Learning Validation for GABA
Zien Ma, S. M. Shermer, Oktay Karaku\c{s}, Frank C. Langbein
https://arxiv.org/abs/2602.20289 https://mastoxiv.page/@arXiv_eessSP_bot/116130267228834775
- Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Appro...
Haochen Zhang, Zhong Zheng, Lingzhou Xue
https://arxiv.org/abs/2602.20297 https://mastoxiv.page/@arXiv_statML_bot/116130255458256497
- Multilevel Determinants of Overweight and Obesity Among U.S. Children Aged 10-17: Comparative Eva...
Joyanta Jyoti Mondal
https://arxiv.org/abs/2602.20303 https://mastoxiv.page/@arXiv_csAI_bot/116130097466859145
- An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes ...
Shyr, Hu, Tinker, Cassini, Byram, Hamid, Fabbri, Wright, Peterson, Bastarache, Xu
https://arxiv.org/abs/2602.20324 https://mastoxiv.page/@arXiv_csAI_bot/116130100089848459
- Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Th...
Jingcheng Yang, Tianhu Xiong, Shengyi Qian, Klara Nahrstedt, Mingyuan Wu
https://arxiv.org/abs/2602.20330 https://mastoxiv.page/@arXiv_csCV_bot/116130463214879334
- No One Size Fits All: QueryBandits for Hallucination Mitigation
Nicole Cho, William Watson, Alec Koppel, Sumitra Ganesh, Manuela Veloso
https://arxiv.org/abs/2602.20332 https://mastoxiv.page/@arXiv_csCL_bot/116130370809116915
- Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Mohanad Obeed, Ming Jian
https://arxiv.org/abs/2602.20361 https://mastoxiv.page/@arXiv_csIT_bot/116130289537785136
- Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
Joel Persson, Jurri\"en Bakker, Dennis Bohle, Stefan Feuerriegel, Florian von Wangenheim
https://arxiv.org/abs/2602.20383 https://mastoxiv.page/@arXiv_statME_bot/116130509065601748
- Selecting Optimal Variable Order in Autoregressive Ising Models
Shiba Biswal, Marc Vuffray, Andrey Y. Lokhov
https://arxiv.org/abs/2602.20394 https://mastoxiv.page/@arXiv_statML_bot/116130299369541741
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(YouTube) Samarth by Hyundai: The vOICe vision BCI in India https://www.youtube.com/watch?v=qtgpoT3eff0&t=692s Will Neuralink Blindsight and other brain implants for restoring vision ever work for congenitally blind people? Probably not.

»Trump und die Tech-Giganten – Das Spiel um Macht:
US Tech-Milliardäre pflegen enge Kontakte zur neuen amerikanischen Regierung. Wie groß ist ihr Einfluss unter Trump?«
Eine klare Zusammenfassung wie US Tech-Konzerne mittels Trump an der Macht sind.
📺 https://www.

Trump und die Tech-Giganten – Das Spiel um Macht - hier anschauen
US Tech-Milliardäre pflegen enge Kontakte zur neuen amerikanischen Regierung. Wie groß ist ihr Einfluss unter Trump? Elon Musk, Peter Thiel, Mark Zuckerberg oder Sam Altmann pflegen enge Kontakte zur neuen amerikanischen Regierung. Wirtschaft, Technologie und Politik verschmelzen in nie dagewesenem Ausmaß. Dabei geht es nicht nur um Deregulierung und große Investitionen, sondern auch um eine neue Vision der Zukunft. Dass Staaten wie Unternehmen geführt werden sollten, zum Beispiel oder, d…

Landmark Vote Positions Helsinki as a Plant-Based Policy Frontrunner https://vegconomist.com/gastronomy-food-service/food-service/landmark-vote-positions-helsinki-as-a-plant-based-policy-frontrunner/

Landmark Vote Positions Helsinki as a Plant-Based Policy Frontrunner - vegconomist - the vegan business magazine
In a decisive move toward a more sustainable food system, the City Council of Helsinki has approved a landmark initiative to cut the city’s procurement of

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/6]:
- Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang
https://arxiv.org/abs/2601.09708 https://mastoxiv.page/@arXiv_csCV_bot/115898618760721320
- Universality of Many-body Projected Ensemble for Learning Quantum Data Distribution
Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima
https://arxiv.org/abs/2601.18637 https://mastoxiv.page/@arXiv_quantph_bot/115967001797773134
- FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning
Haozheng Luo, Zhuolin Jiang, Md Zahid Hasan, Yan Chen, Soumalya Sarkar
https://arxiv.org/abs/2601.19001 https://mastoxiv.page/@arXiv_csCL_bot/115972068838908815
- Analysis of Shuffling Beyond Pure Local Differential Privacy
Shun Takagi, Seng Pei Liew
https://arxiv.org/abs/2601.19154 https://mastoxiv.page/@arXiv_csDS_bot/115971701218309765
- CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models
Weining Fu, Kai Shu, Kui Xu, Qiangfeng Cliff Zhang
https://arxiv.org/abs/2602.02620
- XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas
Sultana, Afsar, Rahu, Singh, Shula, Combs, Forchetti, Asari
https://arxiv.org/abs/2602.04819
- Flow-Based Conformal Predictive Distributions
Trevor Harris
https://arxiv.org/abs/2602.07633 https://mastoxiv.page/@arXiv_statML_bot/116045671088130364
- GOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing
Shih-Fang Chen, Jun-Cheng Chen, I-Hong Jhuo, Yen-Yu Lin
https://arxiv.org/abs/2602.08550 https://mastoxiv.page/@arXiv_csCV_bot/116046486984991360
- UI-Venus-1.5 Technical Report
Venus Team, et al.
https://arxiv.org/abs/2602.09082 https://mastoxiv.page/@arXiv_csCV_bot/116050980295461008
- The Wisdom of Many Queries: Complexity-Diversity Principle for Dense Retriever Training
Xincan Feng, Noriki Nishida, Yusuke Sakai, Yuji Matsumoto
https://arxiv.org/abs/2602.09448 https://mastoxiv.page/@arXiv_csIR_bot/116051022881293649
- Intent Laundering: AI Safety Datasets Are Not What They Seem
Shahriar Golchin, Marc Wetter
https://arxiv.org/abs/2602.16729 https://mastoxiv.page/@arXiv_csCR_bot/116101884238965526
- The Metaphysics We Train: A Heideggerian Reading of Machine Learning
Heman Shakeri
https://arxiv.org/abs/2602.19028 https://mastoxiv.page/@arXiv_csCY_bot/116125225694943789
- Skill-Inject: Measuring Agent Vulnerability to Skill File Attacks
David Schmotz, Luca Beurer-Kellner, Sahar Abdelnabi, Maksym Andriushchenko
https://arxiv.org/abs/2602.20156 https://mastoxiv.page/@arXiv_csCR_bot/116125330557447048
- A Very Big Video Reasoning Suite
Maijunxian Wang, et al.
https://arxiv.org/abs/2602.20159 https://mastoxiv.page/@arXiv_csCV_bot/116125664801070747
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