Tootfinder

I find it kinda funny that the 2020 MacBook Air—my work machine (albeit with 16 GB of RAM)—is now described as being “still capable at handling basic tasks like a champ, including streaming video, browsing, and dealing with documents.”
I haven’t noticed #Emacs slowing down, so what do people do that needs so much more computing power!?

I find it kinda funny that the 2020 MacBook Air—my work machine (albeit with 16 GB of RAM)—is now described as being “still capable at handling basic tasks like a champ, including streaming video, browsing, and dealing with documents.”
I haven’t noticed #Emacs slowing down, so what do people do that needs so much more computing power!?

I find it kinda funny that the 2020 MacBook Air—my work machine (albeit with 16 GB of RAM)—is now described as being “still capable at handling basic tasks like a champ, including streaming video, browsing, and dealing with documents.”
I haven’t noticed #Emacs slowing down, so what do people do that needs so much more computing power!?

Combating Homelessness Stigma with LLMs: A New Multi-Modal Dataset for Bias Detection
Jonathan A. Karr Jr., Benjamin F. Herbst, Ting Hua, Matthew Hauenstein, Georgina Curto, Nitesh V. Chawla
https://arxiv.org/abs/2508.13187

Combating Homelessness Stigma with LLMs: A New Multi-Modal Dataset for Bias Detection
Homelessness is a persistent social challenge, impacting millions worldwide. Over 770,000 people experienced homelessness in the U.S. in 2024. Social stigmatization is a significant barrier to alleviation, shifting public perception, and influencing policymaking. Given that online and city council discourse reflect and influence part of public opinion, it provides valuable insights to identify and track social biases. This research contributes to alleviating homelessness by acting on public opi…

Garden Aloft II ⛲️
空中花园 II ⛲️
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

A very stupid workaround (as explained in the article, this has to be done at the factory to make it an officially different product), with the only goal to make it live harder for EV drivers by not offering card payments.
https://www.electrive.com/2025/08/15…

Bypassing the payment terminal with 49.9 kW: TMH sells HYC49 from Alpitronic - electrive.com
The Mobility House offers the Alpitronic Hypercharger HYC49, a fast charger with a maximum charging capacity of 49.9 kW. The model is actually a HYC50, but it

Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentation
Shumeng Li, Jian Zhang, Lei Qi, Luping Zhou, Yinghuan Shi, Yang Gao
https://arxiv.org/abs/2508.13712

Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentation
Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to generate pseudo labels. Recently, advanced state space models, represented by Mamba, have shown efficient handling of long-range dependencies. This drives us to explore their potential in semi-supervised medical image segmentation. In this paper, we propose a novel Diversity-enhanced Collaborative Mamba framewor…

TracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain
Bohao Chu, Meijie Li, Sameh Frihat, Chengyu Gu, Georg Lodde, Elisabeth Livingstone, Norbert Fuhr
https://arxiv.org/abs/2508.13798

TracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain
While document summarization with LLMs has enhanced access to textual information, concerns about the factual accuracy of these summaries persist, especially in the medical domain. Tracing evidence from which summaries are derived enables users to assess their accuracy, thereby alleviating this concern. In this paper, we introduce TracSum, a novel benchmark for traceable, aspect-based summarization, in which generated summaries are paired with sentence-level citations, enabling users to trace b…

A Garden Aloft ⛲️
空中花园 ⛲️
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Repeating Words for Video-Language Retrieval with Coarse-to-Fine Objectives
Haoyu Zhao, Jiaxi Gu, Shicong Wang, Xing Zhang, Hang Xu, Zuxuan Wu, Yu-Gang Jiang
https://arxiv.org/abs/2508.14812

Repeating Words for Video-Language Retrieval with Coarse-to-Fine Objectives
The explosive growth of video streaming presents challenges in achieving high accuracy and low training costs for video-language retrieval. However, existing methods rely on large-scale pre-training to improve video retrieval performance, resulting in significant computational demands. Additionally, the fine-grained information in videos and texts remains underexplored. To alleviate these problems, we propose a novel framework to learn fine-grained features for better alignment and introduce an…