Tootfinder

U.S. allies are rearming.
At NATO’s annual summit in June, the bloc’s members committed to spending at least 5 percent of their GDP on defense and related infrastructure.
East Asian countries are belatedly building warships and missiles to counter a stronger, more assertive China.
But even as funding rises, factories retool, and arms production ramps up,
one question remains unanswered:
Who will wield all these new weapons?
NATO states have not solved the f…

Who Will Wield All Those Shiny New Weapons?
As defense spending rises and production ramps up, allied armies struggle to fill the ranks.

HyTIP: Hybrid Temporal Information Propagation for Masked Conditional Residual Video Coding
Yi-Hsin Chen, Yi-Chen Yao, Kuan-Wei Ho, Chun-Hung Wu, Huu-Tai Phung, Martin Benjak, J\"orn Ostermann, Wen-Hsiao Peng
https://arxiv.org/abs/2508.02072

HyTIP: Hybrid Temporal Information Propagation for Masked Conditional Residual Video Coding
Most frame-based learned video codecs can be interpreted as recurrent neural networks (RNNs) propagating reference information along the temporal dimension. This work revisits the limitations of the current approaches from an RNN perspective. The output-recurrence methods, which propagate decoded frames, are intuitive but impose dual constraints on the output decoded frames, leading to suboptimal rate-distortion performance. In contrast, the hidden-to-hidden connection approaches, which propaga…

NFL rookie rankings at quarter mark of 2025 season: Abdul Carter, Emeka Egbuka, Tyler Warren top list https://www.nfl.com/news/nfl-rookie-rankings-at-quarter-mark-of-2025-season-abdul-carter-emeka-egbuka-tyler-warren-top-l…

Eye2Recall: Exploring the Design of Enhancing Reminiscence Activities via Eye Tracking-Based LLM-Powered Interaction Experience for Older Adults
Lei Han, Mingnan Wei, Qiongyan Chen, Anqi Wang, Rong Pang, Kefei Liu, Rongrong Chen, David Yip
https://arxiv.org/abs/2508.02232

Eye2Recall: Exploring the Design of Enhancing Reminiscence Activities via Eye Tracking-Based LLM-Powered Interaction Experience for Older Adults
Photo-based reminiscence has the potential to have a positive impact on older adults' reconnection with their personal history and improve their well-being. Supporting reminiscence in older adults through technological implementations is becoming an increasingly important area of research in the fields of HCI and CSCW. However, the impact of integrating gaze and speech as mixed-initiative interactions in LLM-powered reminiscence conversations remains under-explored. To address this, we conducte…

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Ziteng Chen (Infrawaves), Xiaohe Hu (Infrawaves), Menghao Zhang (Beihang University), Yanmin Jia (Infrawaves), Yan Zhang (Infrawaves), Mingjun Zhang (Infrawaves), Da Liu (Infrawaves), Fangzheng Jiao (Beihang University), Jun Chen (Infrawaves), He Liu (Infrawaves), Aohan Zeng (Tsinghua University), Shuaixing Duan (Zhipu AI), Ruya Gu (Infrawaves), Yang Jing (Infrawaves), Bowen Han …

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU training clusters, we encounter several challenges when using NCCL in production, including 1) limited efficiency with costly and cumbersome P2P communication, 2) poor tolerance to frequent RNIC port failures, and 3) insufficient observability of transient collective communication anomalies. To address these issues, we pro…

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey
Qiyuan Liu, Hao Xu, Xuhong Chen, Wei Chen, Yee Whye Teh, Ning Miao
https://arxiv.org/abs/2510.01925

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey
Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune LLMs during reinforcement learning (RL) and help select the best answer from multiple candidates during inference. In this paper, we provide a systematic introduction to RMs, along with a comprehensive survey of their applications in LLM reasoning. We first review fundamental concepts of RMs, including their architectures, training methodologies, an…

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Anne Clark:
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Vision Language Model-based Testing of Industrial Autonomous Mobile Robots
Jiahui Wu, Chengjie Lu, Aitor Arrieta, Shaukat Ali, Thomas Peyrucain
https://arxiv.org/abs/2508.02338 …

Vision Language Model-based Testing of Industrial Autonomous Mobile Robots
Autonomous Mobile Robots (AMRs) are deployed in diverse environments (e.g., warehouses, retail spaces, and offices), where they work alongside humans. Given that human behavior can be unpredictable and that AMRs may not have been trained to handle all possible unknown and uncertain behaviors, it is important to test AMRs under a wide range of human interactions to ensure their safe behavior. Moreover, testing in real environments with actual AMRs and humans is often costly, impractical, and pot…

Colts' Howard retires on heels of Rams showing https://www.espn.com/nfl/story/_/id/46453982/colts-xavien-howard-retires-heels-struggles-vs-rams