Tootfinder

Deep Learning and Matrix Completion-aided IoT Network Localization in the Outlier Scenarios
Sunwoo Kim
https://arxiv.org/abs/2508.18225 https://arxiv.org/p…

Deep Learning and Matrix Completion-aided IoT Network Localization in the Outlier Scenarios
In this paper, we propose a deep learning and matrix completion aided approach for recovering an outlier contaminated Euclidean distance matrix D in IoT network localization. Unlike conventional localization techniques that search the solution over a whole set of matrices, the proposed technique restricts the search to the set of Euclidean distance matrices. Specifically, we express D as a function of the sensor coordinate matrix X that inherently satisfies the unique properties of D, and then …

Russian drone exploded 800 meters from nuclear power plant #shorts: https://benborges.xyz/2025/09/26/russian-drone-exploded-meters-from.html

Docs and interviews: Media Matters is struggling to survive, having racked up ~$15M in legal fees to defend itself from lawsuits by Elon Musk, the FTC, and AGs (New York Times)
https://www.nytimes.com/2025/07/25/us/poli

Under Siege From Trump and Musk, a Top Liberal Group Falls Into Crisis
Scrambling to pay legal fees, Media Matters has dialed back its criticism, trimmed its staff and contemplated closing entirely.

Partial trace relations beyond normal matrices
Pablo Costa Rico, Michael M. Wolf
https://arxiv.org/abs/2507.18278 https://arxiv.org/pdf/2507.18278

Partial trace relations beyond normal matrices
We investigate the relationship between partial traces and their dilations for general complex matrices, focusing on two main aspects: the existence of (joint) dilations and norm inequalities relating partial traces and their dilations. Throughout our analysis, we pay particular attention to rank constraints. We find that every pair of matrices of equal size and trace admits dilations of any rank larger than one. We generalize Audenaert's subadditivity inequality to encompass general matrices, …

Yay Tucson mention in The Onion https://theonion.com/office-adds-area-for-lactating-mothers-to-discreetly-pump-iron/

Evaluating the Evaluators: Metrics for Compositional Text-to-Image Generation
Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad, Niki Sepasian, MohammadAmin Fazli, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban
https://arxiv.org/abs/2509.21227

Evaluating the Evaluators: Metrics for Compositional Text-to-Image Generation
Text-image generation has advanced rapidly, but assessing whether outputs truly capture the objects, attributes, and relations described in prompts remains a central challenge. Evaluation in this space relies heavily on automated metrics, yet these are often adopted by convention or popularity rather than validated against human judgment. Because evaluation and reported progress in the field depend directly on these metrics, it is critical to understand how well they reflect human preferences. …

Seriously one of my anger points. Shipping something to get points on your performance review while inconveniencing (at best) countless customers who were perfectly happy before the change and no happier afterwards.
The software "industry" runs on entirely the wrong metrics, including metrics themselves.
https://cosocial.ca/@timbray/115095936936020151

Doubly Stochastic Matrices and Modified Laplacian Matrices of Graphs
Enide Andrade, Geir Dahl
https://arxiv.org/abs/2509.18773 https://arxiv.org/pdf/2509.1…

Z-Scores: A Metric for Linguistically Assessing Disfluency Removal
Maria Teleki, Sai Janjur, Haoran Liu, Oliver Grabner, Ketan Verma, Thomas Docog, Xiangjue Dong, Lingfeng Shi, Cong Wang, Stephanie Birkelbach, Jason Kim, Yin Zhang, James Caverlee
https://arxiv.org/abs/2509.20319

Z-Scores: A Metric for Linguistically Assessing Disfluency Removal
Evaluating disfluency removal in speech requires more than aggregate token-level scores. Traditional word-based metrics such as precision, recall, and F1 (E-Scores) capture overall performance but cannot reveal why models succeed or fail. We introduce Z-Scores, a span-level linguistically-grounded evaluation metric that categorizes system behavior across distinct disfluency types (EDITED, INTJ, PRN). Our deterministic alignment module enables robust mapping between generated text and disfluent …

GM-Skip: Metric-Guided Transformer Block Skipping for Efficient Vision-Language Models
Lianming Huang, Haibo Hu, Qiao Li, Xin He, Nan Guan, Chun Jason Xue
https://arxiv.org/abs/2508.18227

GM-Skip: Metric-Guided Transformer Block Skipping for Efficient Vision-Language Models
Transformer-based Vision-Language Models (VLMs) have achieved impressive performance on tasks such as image captioning, object recognition, and visual reasoning, but their high computational cost hinders deployment in latency-sensitive applications like autonomous driving. We introduce GM-Skip, a flexible and metric-adaptive framework for Transformer block skipping that accelerates VLM inference while preserving output quality. GM-Skip features a greedy, metric-guided block selection strategy t…