No [CII] or dust detection in two Little Red Dots at z$_{rm spec}$ > 7

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: Mengyuan Xiao, Pascal A. Oesch, Longji Bing, David Elbaz, Jorryt Matthee | Summary: Little Red Dots (LRDs) are compact, point-like sources characterized by their red color and broad Balmer lines, which have been debated to be either dominated by active galactic nuclei (AGN) or dusty star-forming galaxies […]


Continue.. No [CII] or dust detection in two Little Red Dots at z$_{rm spec}$ > 7

Mapping the merging zone of late infall in the AB Aur planet-forming system

Kavli Affiliate: Ruobing Dong | First 5 Authors: Jessica Speedie, Ruobing Dong, Richard Teague, Dominique Segura-Cox, Jaime E. Pineda | Summary: Late infall events challenge the traditional view that planet formation occurs without external influence. Here we present deep ALMA $^{12}$CO $J=2-1$ and SO $J_{N}=5_6-4_5$ observations toward AB Aurigae, a Class II disk system with […]


Continue.. Mapping the merging zone of late infall in the AB Aur planet-forming system

Reweighting and Analysing Event Generator Systematics by Neural Networks on High-Level Features

Kavli Affiliate: Mihoko M. Nojiri | First 5 Authors: Amon Furuichi, Sung Hak Lim, Mihoko M. Nojiri, , | Summary: The state-of-the-art deep learning (DL) models for jet classification use jet constituent information directly, improving performance tremendously. This draws attention to interpretability, namely, the decision-making process, correlations contributing to the classification, and high-level features (HLFs) […]


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Global Neutrino Constraints on the Minimal U(1)$_{L_μ-L_τ}$ Model

Kavli Affiliate: Satoshi Shirai | First 5 Authors: Masahiro Ibe, Satoshi Shirai, Keiichi Watanabe, , | Summary: We examine the minimal U(1)$_{L_mu-L_tau}$ gauge model in light of the latest neutrino data, including neutrino oscillations, cosmological observations, direct mass measurements, and neutrinoless double-beta decay. Using the most conservative oscillation data, we find that normal ordering is […]


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OptMetaOpenFOAM: Large Language Model Driven Chain of Thought for Sensitivity Analysis and Parameter Optimization based on CFD

Kavli Affiliate: Long Zhang | First 5 Authors: Yuxuan Chen, Long Zhang, Xu Zhu, Hua Zhou, Zhuyin Ren | Summary: Merging natural language interfaces with computational fluid dynamics (CFD) workflows presents transformative opportunities for both industry and research. In this study, we introduce OptMetaOpenFOAM – a novel framework that bridges MetaOpenFOAM with external analysis and […]


Continue.. OptMetaOpenFOAM: Large Language Model Driven Chain of Thought for Sensitivity Analysis and Parameter Optimization based on CFD

ReaderLM-v2: Small Language Model for HTML to Markdown and JSON

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Zesheng Shi, Bo Wang, Nan Wang, Han Xiao | Summary: We present ReaderLM-v2, a compact 1.5 billion parameter language model designed for efficient web content extraction. Our model processes documents up to 512K tokens, transforming messy HTML into clean Markdown or JSON formats with high […]


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Beyond Visibility Limits: A DRL-Based Navigation Strategy for Unexpected Obstacles

Kavli Affiliate: Biao Huang | First 5 Authors: Mingao Tan, Shanze Wang, Biao Huang, Zhibo Yang, Rongfei Chen | Summary: Distance-based reward mechanisms in deep reinforcement learning (DRL) navigation systems suffer from critical safety limitations in dynamic environments, frequently resulting in collisions when visibility is restricted. We propose DRL-NSUO, a novel navigation strategy for unexpected […]


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Mapping the ISR Landscape in Cognitive Disorders via single-cell multi-omics

Kavli Affiliate: Peter Walter | Authors: Kristof Torkenczy, Lucas C Reineke, Sean W Dooling, Benjamin W Henderson, Daniel Itzhak, Benjamin Yang, Dongze He, Richard M Myers, Peter Walter, Stefka Tyanova and Mauro Costa-Mattioli | Summary: Persistent activation of the integrated stress response (ISR) is a major driver of cognitive decline in both neurodevelopmental and neurodegenerative […]


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Output Length Effect on DeepSeek-R1’s Safety in Forced Thinking

Kavli Affiliate: Zhuo Li | First 5 Authors: Xuying Li, Zhuo Li, Yuji Kosuga, Victor Bian, | Summary: Large Language Models (LLMs) have demonstrated strong reasoning capabilities, but their safety under adversarial conditions remains a challenge. This study examines the impact of output length on the robustness of DeepSeek-R1, particularly in Forced Thinking scenarios. We […]


Continue.. Output Length Effect on DeepSeek-R1’s Safety in Forced Thinking

Output Length Effect on DeepSeek-R1’s Safety in Forced Thinking

Kavli Affiliate: Zhuo Li | First 5 Authors: Xuying Li, Zhuo Li, Yuji Kosuga, Victor Bian, | Summary: Large Language Models (LLMs) have demonstrated strong reasoning capabilities, but their safety under adversarial conditions remains a challenge. This study examines the impact of output length on the robustness of DeepSeek-R1, particularly in Forced Thinking scenarios. We […]


Continue.. Output Length Effect on DeepSeek-R1’s Safety in Forced Thinking