Tootfinder

Von Miller is set to join his hometown Dallas Cowboys after agreeing to 1-year deal https://www.foxsports.com/articles/nfl/von-miller-is-set-to-join-his-hometown-dallas-cowboys-after-agreeing-to-1year-deal

Notable NFL injuries to monitor as training camps open: Latest on Mahomes, Nabers, Kittle and more

https://www.cbssports.com/nfl/news/nfl-injury-updates-2026-patri…

What Kubiak, Raiders Aim To Establish During Training Camp https://www.si.com/nfl/raiders/onsi/las-vegas-what-kubiak-aim-establish-during-training-camp

What Kubiak, Raiders Aim To Establish During Training Camp https://www.si.com/nfl/raiders/onsi/las-vegas-what-kubiak-aim-establish-during-training-camp

@… wouldn't the deciding factor be how much a language is represented in the LLM training set vs the inherent properties of a language?
BTW it's Yossi Kreinin, not Kreinen

A.J. Brown beats Sauce Gardner in 1-on-1 training camp rep: Reaction draws fiery response from Colts CB

https://www.cbssports.com/nfl/news/a-j-brown-sauce-gardner-training-camp-battle/

If you have spent a night in a US hospital in the past 20 years, the Agency for Healthcare Research and Quality (AHRQ)) was working on your behalf whether you knew it or not.
It built the patient-experience surveys Medicare uses to help set what hospitals are paid.
The quality indicators regulators rely on to spot a hospital that is harming people are its work.
With the defense department, it produced the team-communication training now standard in operating rooms and em…

Trump is laying waste to the agency that keeps hospital patients safe
Few have heard of the Agency for Healthcare Research and Quality, but it has saved tens of thousands of lives and billions of dollars

How Raiders Set Tone Ahead of 2026 Training Camp https://www.si.com/nfl/raiders/onsi/las-vegas-how-set-tone-ahead-2026-training-camp

Forgotten Cowboys RB is Looking Like Next Training Camp Darling https://heavy.com/sports/nfl/dallas-cowboys/cowboys-israel-abanikanda-training-camp-darling/

@… I think you are *correct* in the conclusion that hosting stuff on GitHub *is* putting it in a training set.
But it also feels a bit… tone deaf? To suggest people can’t be upset by that. When I put my project in GitHub a decade ago, that was very much *not* the expectation that was being set. I’m sure you know that.
The deal changed since then yes, and…

Training Camp Notebook 8/6: Kirk Cousins, Fernando Mendoza showcase their strengths https://www.raiders.com/news/training-camp-notebook-8-6-kirk-cousins-fernando-mendoza-showcase-their-strengths

Radu Gheorghe and Rafał Kuć are joining #bbuzz26 to talk about ways to untangle it: lexical search, significant terms, training an embedder from scratch, etc.
Learn more about their amazing session: https://2026.berlinbuzzwords.de/session/circular-dependency-fixes-when-bootstrapping-a-golden-set/
Join us for Berlin Buzzwords on June 7-9 at Kulturbrauerei or online

What We Learned About Dallas Cowboys Before Training Camp https://www.si.com/nfl/cowboys/onsi/what-learned-dallas-cowboys-before-training-camp

Vikings' QB battle: Kevin O'Connell looking for either Kyler Murray or J.J. McCarthy to set 'standard' https://www.nfl.com/news/vikings-qb-battle-kevin-oconnell-standard-kyler-murray-jj-mccarthy

Evaluation-Recording Contamination in Learned Nano-Quadrotor Dynamics: A Fresh-Seed Audit
David Shulman
https://arxiv.org/abs/2607.18482 https://arxiv.org/pdf/2607.18482 https://arxiv.org/html/2607.18482
arXiv:2607.18482v1 Announce Type: new
Abstract: Learned flight-dynamics models are often trained on short windows extracted from longer recordings. Randomly splitting these windows can place dependent samples from the same physical flight in both training and evaluation sets. We audit this issue using a fixed snapshot of the NanoBench Crazyflie 2.1 dataset. The experiment holds evaluation flights, rollout starts, training-window count, validation data, and optimization budget fixed. In the contaminated protocol, [LeakagePercent] percent of a recording-disjoint training set is replaced with windows from evaluation recordings, while both arms use the same clean validation set. We compare a world-coordinate delta multilayer perceptron with a relative-coordinate control across [NumSeeds] fresh training seeds and [NumEvalFlights] complete evaluation recordings. The primary endpoint is failure-aware position RMSE over 1-second rollouts, analyzed with paired crossed recording-by-seed inference. Contamination lowers apparent world-model error by 12.1 percent, from 0.299 m to 0.262 m, but the predeclared 95 percent confidence interval for contaminated minus disjoint error is -0.0735 to 0.0011 m. Because the interval crosses zero, the confirmatory result is negative. Secondary horizons and the relative-coordinate model show similar trends, but no coordinate-representation interaction is supported. Reliable leakage assessment therefore requires recording-level splits, failure-aware rollouts, replication across fresh seeds, and inference over both recordings and optimization seeds.
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Training Camp Notebook 8/6: Kirk Cousins, Fernando Mendoza showcase their strengths https://www.raiders.com/news/training-camp-notebook-8-6-kirk-cousins-fernando-mendoza-showcase-their-strengths

What We Learned About Dallas Cowboys Before Training Camp https://www.si.com/nfl/cowboys/onsi/what-learned-dallas-cowboys-before-training-camp

Hyperspectral Calibration Detection: A Novel Concept For Change Detection With Unsupervised Incremental Safe Pseudo-Labeling Implementation
Chia-Hsiang Lin, Shih-Min Hsu, Ching-Yun Liang, Jocelyn Chanussot, Jhih-Yan Chen
https://arxiv.org/abs/2608.06028 https://arxiv.org/pdf/2608.06028 https://arxiv.org/html/2608.06028
arXiv:2608.06028v1 Announce Type: new
Abstract: Hyperspectral change detection (HCD) has found numerous key applications, such as land cover monitoring. The majority of benchmark HCD algorithms are semi-supervised methods, and some of them can even achieve very low sample labeling rates. However, in some practical scenarios, such as those requiring immediate detection responses for onboard edge computing, we need to achieve the zero-label requirement as ground-truth labeling would not be available onboard for newly acquired images. In this work, we propose a fully unsupervised HCD algorithm, together with a lightweight model, quite suitable for onboard detection missions. Based on an iteratively augmented training set that safely collects some unchanged pixel samples, we learn an iteratively refined spectrum calibration function that eventually compensates the variability of acquisition conditions (often observed in bitemporal images), thereby making the changed pixels easily detectable by analyzing the calibrated spectra. The proposed hyperspectral looping unsupervised calibration and incremental detection (HyperLUCID) algorithm is not only computationally efficient (around 1 to 2 orders of magnitude faster than most benchmark HCD methods), but has also achieved state-of-the-art results (around 93.6% to 97.9% overall accuracy) on several real benchmark HCD datasets. Source codes: https://github.com/IHCLab/HyperLUCID.
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NFL training camps for 2026 season open this week https://www.nfl.com/news/nfl-training-camps-for-2026-season-open-this-week

Where You Tap Matters: A Probe-and-Model Benchmark for Open-Set RF Fingerprinting
Gabriele Oligeri, Savio Sciancalepore, Ingrid Huso, Fatima Al-Mousawi
https://arxiv.org/abs/2607.21564 https://arxiv.org/pdf/2607.21564 https://arxiv.org/html/2607.21564
arXiv:2607.21564v1 Announce Type: new
Abstract: Radio Frequency Fingerprint Identification (RFFI) enables transmitter identification at the physical layer by learning device-specific impairments from received signals, yet the literature is inconsistent about where in the receiver chain those samples should be collected. Since distinct transformations are applied to the signal by the different receiver operations, i.e., carrier recovery, gain normalization, pulse shaping, and timing recovery, they can either tighten within-transmitter variability or suppress the features RFFI requires for classification. We present a systematic real-world evaluation of open-set, reconstruction-error RFFI using data collected at five probe points along a standard BPSK receiver chain. Our results show that RFFI is strongly probe-dependent: timing recovery and, to a lesser extent, carrier recovery enable low false-acceptance operation with limited in-distribution-out-of-distribution overlap, whereas other stages often require a false-acceptance ratio above 0.1 to achieve a true-acceptance ratio of 0.9. To test the validity of our findings across model selection, we benchmark several LLM-designed autoencoders using a controlled pipeline that holds preprocessing and MSE scoring fixed. These architectures confirm that RFFI is probe-dependent. Moreover, they do not outperform the baseline at the chosen operating point and typically increase training time. Overall, probe selection dominates reconstruction-based open-set RFFI performance, more than the autoencoder complexity.
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Cowboys to report to training camp July 28; joint practice dates also set https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2026/06/22/cowboys-training-camp-report-date-july-28-joint-practi…

Baker Mayfield feels 'disrespected' by lack of contract extension ahead of training camp

https://www.cbssports.com/nfl/news/baker-mayfield-disre…

@… And, at this point, yes I won’t submit anything new to GitHub. But there’s probably little value in explicitly deleting what is already there.
Like you said, it’s already in the training set. That damage is done, and I’m upset about it.

6 Most Important Storylines Entering Dallas Cowboys Training Camp https://www.si.com/nfl/cowboys/onsi/most-important-storylines-dallas-cowboys-2026-nfl-training-camp

NFL training camps set to open with 10 new head coaches, several QB changes and plenty of hope https://www.foxsports.com/articles/nfl/nfl-training-camps-set-to-open-with-10-new-head-coaches-several-qb-changes-and-…

Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift
Bong Gyun Shin, Chan Sik Lee, Hyesun Suh
https://arxiv.org/abs/2605.21507 https://arxiv.org/pdf/2605.21507 https://arxiv.org/html/2605.21507
arXiv:2605.21507v1 Announce Type: new
Abstract: Atmospheric visibility is a critical variable for transportation safety and air quality management, however, accurate prediction remains challenging due to the complex interactions between meteorological conditions and air pollutants, as well as the rarity of low-visibility events. This study introduces a machine learning framework to nowcast visibility in six major South Korean cities. To handle the imbalance in the 2018-2020 training data, we applied the Synthetic Minority Over-sampling Technique with Nominal and Continuous (SMOTENC) and Conditional Tabular Generative Adversarial Network (CTGAN). An ensemble approach combining machine learning and deep learning models was then used and evaluated on a 2021 test dataset. The results revealed a marked decline in predictive performance in the test set compared to the cross-validation phase. This degradation was attributed to a distributional shift between training and testing periods, which was quantitatively confirmed by measuring the Wasserstein distance of the most influential feature identified by SHAP analysis. In general, this study presents a methodology that aims to simultaneously address the dual challenges of data imbalance and temporal distributional shifts, and emphasizes the necessity of accounting for evolving external environmental factors when implementing nowcasting models on time-series data.
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4 Dallas Cowboys X-Factors During 2026 Training Camp https://www.si.com/nfl/cowboys/onsi/4-dallas-cowboys-x-factors-during-2026-training-camp

4 Dallas Cowboys X-Factors During 2026 Training Camp https://www.si.com/nfl/cowboys/onsi/4-dallas-cowboys-x-factors-during-2026-training-camp

Raiders Training Camp Roster: Full 90-Man Roster Entering Camp https://www.si.com/nfl/raiders/onsi/las-vegas-training-camp-roster-full-90-man-entering-camp

All Eyes Are on $28.9 Million Playmaker at Cowboys Training Camp https://heavy.com/sports/nfl/dallas-cowboys/caleb-downs-dallas-cowboys-training-camp/

When and where are the Dallas Cowboys spending training camp in 2026? https://bolavip.com/en/nfl/when-and-where-are-the-dallas-cowboys-spending-training-camp-in-2026

Raiders add defensive end, linebacker, receiver with camp set to start https://www.reviewjournal.com/sports/raiders/raiders-add-defensive-end-linebacker-receiver-with-camp-set-to-start-3855741/

How to Attend Dallas Cowboys Training Camp: Tickets, Parking and Fan Guide https://www.si.com/nfl/cowboys/onsi/how-to-attend-dallas-cowboys-training-camp-tickets-parking-fan-guide

Vita Vea requests trade from Buccaneers ahead of training camp: Source https://www.nytimes.com/athletic/7473902/2026/07/27/vita-vea-trade-request-buccaneers-nfl/

How to Attend Dallas Cowboys Training Camp: Tickets, Parking and Fan Guide https://www.si.com/nfl/cowboys/onsi/how-to-attend-dallas-cowboys-training-camp-tickets-parking-fan-guide

Patriots set to begin training camp on a Saturday ... https://www.espn.com/nfl/story/_/id/49385736/new-england-patriots-starts-2026-training-camp-saturday-drake-maye

Toward a mechanistic understanding of inference in visual cortex and diffusion models
Zeyu Yun, Alexander Belsten, Dasheng Bi, Zahra Kadkhodaie, Yubei Chen, Bruno A. Olshausen
https://arxiv.org/abs/2607.15693 https://arxiv.org/pdf/2607.15693 https://arxiv.org/html/2607.15693
arXiv:2607.15693v1 Announce Type: new
Abstract: We describe a model of perceptual inference in primary visual cortex (V1) equivalent to a minimal diffusion model whose function can be readily understood from its parameters. The model is based on sparse coding with a non-factorial prior over latent variables in the form of an unconstrained, pairwise interaction matrix, extending standard sparse coding inference to a general recurrent dynamical system. We efficiently train these recurrent dynamics using a denoising score-matching objective and implicit differentiation. After training on natural images, the learned interaction matrix mirrors the structure of horizontal connections in superficial layers of V1 that link neurons of similar orientation tuning. This model exhibits exceptionally good denoising performance, restoring image features such as extended contours amid extreme visual ambiguity, nearly matching the behavior of standard, black-box diffusion architectures in generalization regime. Owing to the model's simplicity, the network's Jacobian can be decomposed directly in terms of the interaction matrix between latent variables, revealing mechanistically how the recurrent dynamics assign high probability over a continuous family of natural structural deformations. Intriguingly, within this circuit, a large fraction of latent variables learn to disconnect from visual input altogether, essentially forming a hierarchical representation that appears to enforce global consistency among image features. Together, the model and results bridge two distinct domains: for neuroscience, it generates concrete, testable hypotheses regarding functional connectivity in recurrent neural circuits during perceptual inference tasks; for machine learning, it elucidates the internal mechanisms learned by diffusion models that allow them to generate infinitely many novel images from a finite training set.
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New DB Taron Johnson is bringing leadership to Raiders young secondary https://raiderswire.usatoday.com/story/sports/nfl/raiders/2026/08/06/new-db-taron-johnson-is-bringing-leadership-to-raider…

Estimating stellar metallicities from Gaia DR3 XP data using LAMOST DR10
Divyansh Srivastava, Andrzej Niedzielski, Rodolfo Smiljanic
https://arxiv.org/abs/2607.18707 https://arxiv.org/pdf/2607.18707 https://arxiv.org/html/2607.18707
arXiv:2607.18707v1 Announce Type: new
Abstract: Gaia DR3 provides astrophysical parameters for hundreds of millions of stars, but the metallicities [M/H] from its GSP-Phot module suffer from systematic biases. We estimate stellar metallicities from Gaia DR3 data using the homogeneous spectroscopic iron abundances [Fe/H] of LAMOST DR10 as training labels. We cross-matched LAMOST DR10 with Gaia DR3 and trained a gradient-boosted decision-tree regressor (XGBoost) on 1.20 million AFGK stars using only Gaia-derived inputs and proxies. We validated the estimates on held-out LAMOST stars, GALAH DR4, APOGEE DR17, and 46 open clusters, and applied the model to measure the radial metallicity gradient of the Milky Way disk. On the held-out test set, the model achieves a mean absolute error of 0.052 dex and $R^2=0.94$ with negligible bias, compared with 0.242 dex for GSP-Phot on the same stars. The estimates transfer well to external surveys, with mean absolute errors of 0.066 dex for GALAH and 0.068 dex for APOGEE. For open clusters, the median difference between our estimated [Fe/H] and spectroscopic values is 0.041 dex, smaller than both GSP-Phot (0.248 dex) and a previous APOGEE-trained XGBoost model (0.067 dex). Applied to the Galactic disk, our model recovers a broken thin-disk radial gradient, with inner and outer slopes of $ 0.119$ and $-0.058\,\mathrm{dex\,kpc^{-1}}$, respectively, and a break near 5.9 kpc, as well as an open-cluster gradient of $-0.066\,\mathrm{dex\,kpc^{-1}}$; both agree with previous high-resolution spectroscopic studies. Our [Fe/H] estimates are accurate to 0.05-0.07 dex for AFGK stars with $[\mathrm{Fe/H}]\gtrsim-2.5$; below this limit, the predictions should be treated as lower bounds. The catalogue and trained model are publicly available on Zenodo and are suitable for chemical studies of the Milky Way.
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Klint Kubiak says full roster of Raiders players ready day one of camp https://raiderswire.usatoday.com/story/sports/nfl/raiders/2026/07/28/klint-kubiak-full-raiders-roster-read…

Cowboys Make Decision on Key Starting Blocker at Camp https://heavy.com/sports/nfl/dallas-cowboys/tyler-guyton-nate-thomas-brian-schottenheimer/

Deebo Samuel: I still have 'at least three, four good years left' https://www.nfl.com/news/deebo-samuel-i-still-have-at-least-three-four-good-years-left

NFC East News: Revamped Linebacker Rooms and New Defensive Coordinators Reshaping the Division https://www.si.com/nfl/commanders/onsi/nfc-east-news-roundup-cowboys-eagles-giants-commanders-links

Predicting Dallas Cowboys 53-Man Roster Entering July https://www.si.com/nfl/cowboys/onsi/predicting-dallas-cowboys-53-man-roster-entering-july

Predicting Dallas Cowboys 53-Man Roster Entering July https://www.si.com/nfl/cowboys/onsi/predicting-dallas-cowboys-53-man-roster-entering-july

5 home-grown Raiders on their final shot in Las Vegas https://raiderswire.usatoday.com/story/sports/nfl/raiders/2026/07/22/5-home-grown-raiders-final-shot-make-or-break-2026-las-vegas/91012120007/…

Dallas Cowboys Veterans Who Could Lose Their Starting Jobs This Summer https://www.si.com/nfl/cowboys/onsi/dallas-cowboys-veterans-who-could-lose-starting-jobs-this-summer

Joe Milton Named Cowboys Top Trade Candidate Entering 2026 Season https://www.si.com/nfl/cowboys/onsi/joe-milton-named-dallas-cowboys-top-trade-candidate-entering-2026-season

Dallas Cowboys Veterans Who Could Lose Their Starting Jobs This Summer https://www.si.com/nfl/cowboys/onsi/dallas-cowboys-veterans-who-could-lose-starting-jobs-this-summer