Tootfinder

Commanders signing Titans 2022 first-round pick Treylon Burks to practice squad https://www.nfl.com/news/commanders-signing-titans-2022-first-round-pick-treylon-burks-to-practice-squad

Semi-MoE: Mixture-of-Experts meets Semi-Supervised Histopathology Segmentation
Nguyen Lan Vi Vu, Thanh-Huy Nguyen, Thien Nguyen, Daisuke Kihara, Tianyang Wang, Xingjian Li, Min Xu
https://arxiv.org/abs/2509.13834

Semi-MoE: Mixture-of-Experts meets Semi-Supervised Histopathology Segmentation
Semi-supervised learning has been employed to alleviate the need for extensive labeled data for histopathology image segmentation, but existing methods struggle with noisy pseudo-labels due to ambiguous gland boundaries and morphological misclassification. This paper introduces Semi-MOE, to the best of our knowledge, the first multi-task Mixture-of-Experts framework for semi-supervised histopathology image segmentation. Our approach leverages three specialized expert networks: A main segmentati…

🇺🇦 #NowPlaying on KEXP's #EasternEchoes
SE SO NEON:
🎵 Jayu
#SESONEON
https://sesoneon.bandcamp.com/track/jayu
https://open.spotify.com/track/5KnwqkmR7bjLIvQUNwX2Yq

Centrist Republicans revolt, signing a petition to force a vote on Obamacare funding (NBC News)
https://www.nbcnews.com/politics/congress/centrist-republicans-revolt-signing-petition-force-vote-obamacare-fund-rcna249693
http://www.memeorandum.com/251217/p74#a251217p74

Cowboys Eyed as a Top Team for Speedy Former $20 Million 42-Game Starter https://heavy.com/sports/nfl/dallas-cowboys/nfl-rumors-news-signings-packers-giants-cardinals/?adt_ei=[email]

Source: Commanders picking up WR Burks https://www.espn.com/nfl/story/_/id/46620380/source-commanders-signing-treylon-burks-practice-squad

Masked Feature Modeling Enhances Adaptive Segmentation
Wenlve Zhou, Zhiheng Zhou, Tiantao Xian, Yikui Zhai, Weibin Wu, Biyun Ma
https://arxiv.org/abs/2509.13801 https://

Masked Feature Modeling Enhances Adaptive Segmentation
Unsupervised domain adaptation (UDA) for semantic segmentation aims to transfer models from a labeled source domain to an unlabeled target domain. While auxiliary self-supervised tasks-particularly contrastive learning-have improved feature discriminability, masked modeling approaches remain underexplored in this setting, largely due to architectural incompatibility and misaligned optimization objectives. We propose Masked Feature Modeling (MFM), a novel auxiliary task that performs feature mas…

🇺🇦 #NowPlaying on KEXP's #ElSonido
Shego:
🎵 Manifesting
#Shego
https://shegomanda.bandcamp.com/track/manifesting
https://open.spotify.com/track/0AXUs1lltykWsdkxnmzkvK

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation
Jiyun Im, SuBeen Lee, Miso Lee, Jae-Pil Heo
https://arxiv.org/abs/2509.13907 https://

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation
Few-Shot 3D Point Cloud Segmentation (FS-PCS) aims to predict per-point labels for an unlabeled point cloud, given only a few labeled examples. To extract discriminative representations from the limited support set, existing methods have constructed prototypes using conventional algorithms such as farthest point sampling. However, we point out that its initial randomness significantly affects FS-PCS performance and that the prototype generation process remains underexplored despite its prevalen…

Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation
Puru Vaish, Felix Meister, Tobias Heimann, Christoph Brune, Jelmer M. Wolterink
https://arxiv.org/abs/2509.13846

Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation
Many recent approaches in representation learning implicitly assume that uncorrelated views of a data point are sufficient to learn meaningful representations for various downstream tasks. In this work, we challenge this assumption and demonstrate that meaningful structure in the latent space does not emerge naturally. Instead, it must be explicitly induced. We propose a method that aligns representations from different views of the data to align complementary information without inducing false…