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Apple Watch – eine Uhr für (fast) alle Fälle | Mac & i-Podcast
Vom holprigen Start über Health-Meilensteine und enttäuschte Erwartungen bis zu Alltagsnutzen und Problemstellen: höchste Zeit für eine Apple-Watch-Episode.

Multi-Physics: A Comprehensive Benchmark for Multimodal LLMs Reasoning on Chinese Multi-Subject Physics Problems
Zhongze Luo, Zhenshuai Yin, Yongxin Guo, Zhichao Wang, Jionghao Zhu, Xiaoying Tang
https://arxiv.org/abs/2509.15839

Multi-Physics: A Comprehensive Benchmark for Multimodal LLMs Reasoning on Chinese Multi-Subject Physics Problems
While multimodal LLMs (MLLMs) demonstrate remarkable reasoning progress, their application in specialized scientific domains like physics reveals significant gaps in current evaluation benchmarks. Specifically, existing benchmarks often lack fine-grained subject coverage, neglect the step-by-step reasoning process, and are predominantly English-centric, failing to systematically evaluate the role of visual information. Therefore, we introduce \textbf {Multi-Physics} for Chinese physics reasonin…

SOMEONE'S GONNA GET HAAAACKED still unpatched after 6 months...
Original post: #cybersecurity

Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Division
Jaros{\l}aw Byrka, Franciszek Malinka, Tomasz Ponitka
https://arxiv.org/abs/2507.14957

Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Division
We study the fair division of indivisible items and provide new insights into the EFX problem, which is widely regarded as the central open question in fair division, and the PMMS problem, a strictly stronger variant of EFX. Our first result constructs a three-agent instance with two monotone valuations and one additive valuation in which no PMMS allocation exists. Since EFX allocations are known to exist under these assumptions, this establishes a formal separation between EFX and PMMS. We p…

CCL-XCoT: An Efficient Cross-Lingual Knowledge Transfer Method for Mitigating Hallucination Generation
Weihua Zheng, Roy Ka-Wei Lee, Zhengyuan Liu, Kui Wu, AiTi Aw, Bowei Zou
https://arxiv.org/abs/2507.14239

CCL-XCoT: An Efficient Cross-Lingual Knowledge Transfer Method for Mitigating Hallucination Generation
Multilingual Large Language Models(MLLMs) demonstrate strong generalization across languages, yet they remain prone to hallucinations, especially in low-resource languages, due to training data imbalances. These hallucinations, which include inaccurate or fabricated outputs, are particularly problematic in domain-specific generation tasks (Chataigner et al., 2024). To address this challenge, we propose CCL-XCoT(Curriculum-based Contrastive Learning-based Cross-lingual Chain-of-Thought), a two-s…

COMPASS: A Multi-Dimensional Benchmark for Evaluating Code Generation in Large Language Models
James Meaden, Micha{\l} Jarosz, Piotr Jod{\l}owski, Grigori Melnik
https://arxiv.org/abs/2508.13757

COMPASS: A Multi-Dimensional Benchmark for Evaluating Code Generation in Large Language Models
Current code generation benchmarks focus primarily on functional correctness while overlooking two critical aspects of real-world programming: algorithmic efficiency and code quality. We introduce COMPASS (COdility's Multi-dimensional Programming ASSessment), a comprehensive evaluation framework that assesses code generation across three dimensions: correctness, efficiency, and quality. COMPASS consists of 50 competitive programming problems from real Codility competitions, providing authentic …

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光与影 🔅
📷 Minolta Hi-Matic AF
🎞️ILFORD FP4 Plus, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography …

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Online Multi-Robot Coordination and Cooperation with Task Precedence Relationships
Walker Gosrich, Saurav Agarwal, Kashish Garg, Siddharth Mayya, Matthew Malencia, Mark Yim, Vijay Kumar
https://arxiv.org/abs/2509.15052

Online Multi-Robot Coordination and Cooperation with Task Precedence Relationships
We propose a new formulation for the multi-robot task allocation problem that incorporates (a) complex precedence relationships between tasks, (b) efficient intra-task coordination, and (c) cooperation through the formation of robot coalitions. A task graph specifies the tasks and their relationships, and a set of reward functions models the effects of coalition size and preceding task performance. Maximizing task rewards is NP-hard; hence, we propose network flow-based algorithms to approximat…

The Milky Way is a less massive galaxy--new estimates of the Milky Way's local and global stellar masses
Jianhui Lian (Yunnan Uni.), Tao Wang (Yunnan Uni.), Qikang Feng (Peking Uni.), Yang Huang (U of Chinese Academy of Sciences), Helong Guo (Yunnan Uni.)
https://arxiv.org/abs/2508.13665

The Milky Way is a less massive galaxy--new estimates of the Milky Way's local and global stellar masses
Stellar mass is the most fundamental property of a galaxy. While it has been robustly measured for millions of external galaxies, it remains poorly constrained for the Milky Way because of the strong selection effect from our inside perspective. In this work, we reconstruct the intrinsic vertical mass density profile in the solar neighborhood and the radial mass density profile across the entire Galaxy using data from the Gaia and APOGEE surveys, following careful correction for the selection f…

Automating Steering for Safe Multimodal Large Language Models
Lyucheng Wu, Mengru Wang, Ziwen Xu, Tri Cao, Nay Oo, Bryan Hooi, Shumin Deng
https://arxiv.org/abs/2507.13255

Automating Steering for Safe Multimodal Large Language Models
Recent progress in Multimodal Large Language Models (MLLMs) has unlocked powerful cross-modal reasoning abilities, but also raised new safety concerns, particularly when faced with adversarial multimodal inputs. To improve the safety of MLLMs during inference, we introduce a modular and adaptive inference-time intervention technology, AutoSteer, without requiring any fine-tuning of the underlying model. AutoSteer incorporates three core components: (1) a novel Safety Awareness Score (SAS) that …