Tootfinder

Cowboys Minicamp: don't buy into early hype on Jonathan Mingo, Joe Milton https://insidethestar.com/cowboys-minicamp-dont-buy-into-early-hype-on-jonathan-mingo-joe-milton

Unreal is all you need: Multimodal ISAC Data Simulation with Only One Engine
Kongwu Huang, Shiyi Mu, Jun Jiang, Yuan Gao, Shugong Xu
https://arxiv.org/abs/2507.08716

Unreal is all you need: Multimodal ISAC Data Simulation with Only One Engine
Scaling laws have achieved success in LLM and foundation models. To explore their potential in ISAC research, we propose Great-X. This single-engine multimodal data twin platform reconstructs the ray-tracing computation of Sionna within Unreal Engine and is deeply integrated with autonomous driving tools. This enables efficient and synchronized simulation of multimodal data, including CSI, RGB, Radar, and LiDAR. Based on this platform, we construct an open-source, large-scale, low-altitude UAV …

Apple TV: Neues Modell noch in diesem Jahr?
Apple plant vermutlich noch in diesem Jahr eine frische Multimediabox. Es könnte dieses Mal neue Hardware-Elemente geben.
https://www.heise.de/news/Apple-T…

Could Packers WR Bo Melton be two-way contributor? 'I like to run for days' https://www.nfl.com/news/could-packers-wr-bo-melton-be-two-way-contributor-i-like-to-run-for-days

Multilingual Multimodal Software Developer for Code Generation
Linzheng Chai, Jian Yang, Shukai Liu, Wei Zhang, Liran Wang, Ke Jin, Tao Sun, Congnan Liu, Chenchen Zhang, Hualei Zhu, Jiaheng Liu, Xianjie Wu, Ge Zhang, Tianyu Liu, Zhoujun Li
https://arxiv.org/abs/2507.08719

Multilingual Multimodal Software Developer for Code Generation
The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and flowcharts used in real-world software development. To bridge this gap, we introduce MM-Coder, a Multilingual Multimodal software developer. MM-Coder integrates visual design inputs-Unified Modeling Language (UML) diagrams and flowcharts (termed Visual Workflow)-with textual instructions to enhance code generation ac…

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Emanuel Hubenschmid, Guido Burkard
https://arxiv.org/abs/2506.10483

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Recent progress in ultrafast optics facilitates the investigation of the dynamics of highly multimode quantum states of light, as demonstrated by the application of electro-optic sampling to quantum states of the electromagnetic field. Yet, the complete tomographic reconstruction of optical quantum states with prior unknown statistics and dynamics is still challenging, since state-of-the-art tomographic methods require the measurement of many orthogonal, distinguishable modes. Here, we propose …

Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment
Tianyu Chen, Jian Lou, Wenjie Wang
https://arxiv.org/abs/2506.10030 https:/…

Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment
As Retrieval-Augmented Generation (RAG) evolves into service-oriented platforms (Rag-as-a-Service) with shared knowledge bases, protecting the copyright of contributed data becomes essential. Existing watermarking methods in RAG focus solely on textual knowledge, leaving image knowledge unprotected. In this work, we propose AQUA, the first watermark framework for image knowledge protection in Multimodal RAG systems. AQUA embeds semantic signals into synthetic images using two complementary meth…

WDMIR: Wavelet-Driven Multimodal Intent Recognition
Weiyin Gong, Kai Zhang, Yanghai Zhang, Qi Liu, Xinjie Sun, Junyu Lu, Linbo Zhu
https://arxiv.org/abs/2506.10011

WDMIR: Wavelet-Driven Multimodal Intent Recognition
Multimodal intent recognition (MIR) seeks to accurately interpret user intentions by integrating verbal and non-verbal information across video, audio and text modalities. While existing approaches prioritize text analysis, they often overlook the rich semantic content embedded in non-verbal cues. This paper presents a novel Wavelet-Driven Multimodal Intent Recognition(WDMIR) framework that enhances intent understanding through frequency-domain analysis of non-verbal information. To be more spe…

ByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
Rajarshi Roy, Devleena Das, Ankesh Banerjee, Arjya Bhattacharjee, Kousik Dasgupta, Subarna Tripathi
https://arxiv.org/abs/2507.08679

ByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
We introduce ByDeWay, a training-free framework designed to enhance the performance of Multimodal Large Language Models (MLLMs). ByDeWay uses a novel prompting strategy called Layered-Depth-Based Prompting (LDP), which improves spatial reasoning and grounding without modifying any model parameters. It segments the scene into closest, mid-range, and farthest layers using monocular depth estimation, then generates region-specific captions with a grounded vision-language model. These structured, d…

Is he a WR or CB? Packers' Bo Melton could answer yes to both https://www.espn.com/nfl/story/_/id/45494234/nfl-green-bay-packers-bo-melton-max-cornerback-receiver-minicamp