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📏 Optical frequency comb integration transforms absolute distance measurement precision
https://phys.org/news/2025-07-optical-frequency-absolute-distance-precision.html

Optical frequency comb integration transforms absolute distance measurement precision
The Korea Research Institute of Standards and Science has successfully developed a length measurement system that achieves a level of precision approaching the theoretical limit allowed by quantum physics.

Controlling Multimodal LLMs via Reward-guided Decoding
Oscar Ma\~nas, Pierluca D'Oro, Koustuv Sinha, Adriana Romero-Soriano, Michal Drozdzal, Aishwarya Agrawal
https://arxiv.org/abs/2508.11616

Controlling Multimodal LLMs via Reward-guided Decoding
As Multimodal Large Language Models (MLLMs) gain widespread applicability, it is becoming increasingly desirable to adapt them for diverse user needs. In this paper, we study the adaptation of MLLMs through controlled decoding. To achieve this, we introduce the first method for reward-guided decoding of MLLMs and demonstrate its application in improving their visual grounding. Our method involves building reward models for visual grounding and using them to guide the MLLM's decoding process. Co…

Case-Based Decision-Theoretic Decoding with Quality Memories
Hiroyuki Deguchi, Masaaki Nagata
https://arxiv.org/abs/2509.12677 https://arxiv.org/pdf/2509.1…

Case-Based Decision-Theoretic Decoding with Quality Memories
Minimum Bayes risk (MBR) decoding is a decision rule of text generation, which selects the hypothesis that maximizes the expected utility and robustly generates higher-quality texts than maximum a posteriori (MAP) decoding. However, it depends on sample texts drawn from the text generation model; thus, it is difficult to find a hypothesis that correctly captures the knowledge or information of out-of-domain. To tackle this issue, we propose case-based decision-theoretic (CBDT) decoding, another…

On the error correction of iterative bounded distance decoding of generalized LDPC codes
David Burshtein
https://arxiv.org/abs/2507.12073 https://

On the error correction of iterative bounded distance decoding of generalized LDPC codes
Consider an ensemble of regular generalized LDPC (GLDPC) codes and assume that the same component code is associated with each parity check node. To decode a GLDPC code from the ensemble, we use the bit flipping bounded distance decoding algorithm, which is an extension of the bit flipping algorithm for LDPC codes. Previous work has shown conditions, under which, for a typical code in the ensemble with blocklength sufficiently large, a positive constant fraction of worst case errors can be corr…

Evidence for inverse Compton scattering in high-redshift Lyman-break galaxies: #galaxies reveal hidden effect from Big Bang: https://www.physics.ox.ac.uk/news/distant-galaxies-reveal-hidden-effect-big-bang

CDFlow: Generative Gradient Flows for Configuration Space Distance Fields via Neural ODEs
Mengzhu Li, Yunyu Zhou, He Ying, F. Richard Yu
https://arxiv.org/abs/2509.13771 https:/…

CDFlow: Generative Gradient Flows for Configuration Space Distance Fields via Neural ODEs
Signed Distance Fields (SDFs) are a fundamental representation in robot motion planning. Their configuration-space counterpart, the Configuration Space Distance Field (CDF), directly encodes distances in joint space, offering a unified representation for optimization and control. However, existing CDF formulations face two major challenges in high-degree-of-freedom (DoF) robots: (1) they effectively return only a single nearest collision configuration, neglecting the multi-modal nature of minim…

Wie bedroht die #Dürre im Südwesten Nordamerikas die #Landwirtschaft und #Trinkwasserversorgung? Können

Kipppunkt im Südwesten Nordamerikas? Dürre bedroht Landwirtschaft und Trinkwasserversorgung
Der Klimawandel führt zu extremen Dürren im Südwesten Nordamerikas. Das gefährdet die Landwirtschaft, die Trinkwasserversorgung und die Lebensgrundlage der Bevölkerung.

PTSM: Physiology-aware and Task-invariant Spatio-temporal Modeling for Cross-Subject EEG Decoding
Changhong Jing, Yan Liu, Shuqiang Wang, Bruce X. B. Yu, Gong Chen, Zhejing Hu, Zhi Zhang, Yanyan Shen
https://arxiv.org/abs/2508.11357

PTSM: Physiology-aware and Task-invariant Spatio-temporal Modeling for Cross-Subject EEG Decoding
Cross-subject electroencephalography (EEG) decoding remains a fundamental challenge in brain-computer interface (BCI) research due to substantial inter-subject variability and the scarcity of subject-invariant representations. This paper proposed PTSM (Physiology-aware and Task-invariant Spatio-temporal Modeling), a novel framework for interpretable and robust EEG decoding across unseen subjects. PTSM employs a dual-branch masking mechanism that independently learns personalized and shared spat…

Tricyclic graphs for which the second largest distance eigenvalue less than $-\frac{1}{2}$
Kexin Yang, Ligong Wang
https://arxiv.org/abs/2509.12640 https://

Tricyclic graphs for which the second largest distance eigenvalue less than $-\frac{1}{2}$
Let $G$ be a simple connected graph with vertex set $V(G)=\{v_{1}, v_{2}, \ldots, v_{n}\}$. The distance $d_G(v_i,v_j)$ between two vertices $v_i$ and $v_j$ of $G$ is the length of a shortest path between $v_i$ and $v_j$. The distance matrix of $G$ is defined as $D(G)=(d_G(v_i,v_j))_{n\times n}$. The second largest distance eigenvalue of \( G \) is the second largest eigenvalues of $D(G)$. Guo and Zhou [Discrete Math. 347(2024), 114082] proved that any connected graph with the second largest di…