Heterogeneity in Women’s Nighttime Ride-Hailing Intention: Evidence from an LC-ICLV Model Analysis

Kavli Affiliate: Ke Wang | First 5 Authors: , , , , | Summary: While ride-hailing services offer increased travel flexibility and convenience, persistent nighttime safety concerns significantly reduce women’s willingness to use them. Existing research often treats women as a homogeneous group, neglecting the heterogeneity in their decision-making processes. To address this gap, this […]


Continue.. Heterogeneity in Women’s Nighttime Ride-Hailing Intention: Evidence from an LC-ICLV Model Analysis

Fundamental Physics with Pulsars around Sagittarius A$^star$

Kavli Affiliate: Lijing Shao | First 5 Authors: Lijing Shao, Lijing Shao, , , | Summary: Searching for radio pulsars orbiting around the Galactic centre black hole (BH), Sagittarius A$^star$ (Sgr A$^star$), represents a holy grail goal for large-area radio telescopes, in particular for the Square Kilometre Array. Follow-up timing observation of such a PSR-Sgr […]


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Lay2Story: Extending Diffusion Transformers for Layout-Togglable Story Generation

Kavli Affiliate: Jing Wang | First 5 Authors: Ao Ma, Ao Ma, , , | Summary: Storytelling tasks involving generating consistent subjects have gained significant attention recently. However, existing methods, whether training-free or training-based, continue to face challenges in maintaining subject consistency due to the lack of fine-grained guidance and inter-frame interaction. Additionally, the scarcity […]


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WideSearch: Benchmarking Agentic Broad Info-Seeking

Kavli Affiliate: Ke Wang | First 5 Authors: Ryan Wong, Ryan Wong, , , | Summary: From professional research to everyday planning, many tasks are bottlenecked by wide-scale information seeking, which is more repetitive than cognitively complex. With the rapid development of Large Language Models (LLMs), automated search agents powered by LLMs offer a promising […]


Continue.. WideSearch: Benchmarking Agentic Broad Info-Seeking

WideSearch: Benchmarking Agentic Broad Info-Seeking

Kavli Affiliate: Ke Wang | First 5 Authors: Ryan Wong, Ryan Wong, , , | Summary: From professional research to everyday planning, many tasks are bottlenecked by wide-scale information seeking, which is more repetitive than cognitively complex. With the rapid development of Large Language Models (LLMs), automated search agents powered by LLMs offer a promising […]


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GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Kavli Affiliate: Ke Wang | First 5 Authors: GLM-4. 5 Team, GLM-4. 5 Team, , , | Summary: We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that supports both thinking and direct response modes. Through multi-stage training on 23T tokens […]


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Bayesian online collective anomaly and change point detection in fine-grained time series

Kavli Affiliate: Xian Chen | First 5 Authors: Xian Chen, Xian Chen, , , | Summary: Fine-grained time series data are crucial for accurate and timely online change detection. While both collective anomalies and change points can coexist in such data, their joint online detection has received limited attention. In this research, we develop a […]


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Physical properties of galaxies and the UV Luminosity Function from $zsim6$ to $zsim14$ in COSMOS-Web

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: Maximilien Franco, Maximilien Franco, , , | Summary: We present measurements of the rest-frame ultraviolet luminosity function (UVLF) in three redshift bins over $zsim5.5$-14 from the JWST COSMOS-Web survey. Our samples, selected using the dropout technique in the HST/ACS F814W, JWST/NIRCam F115W, and F150W filters, contain a […]


Continue.. Physical properties of galaxies and the UV Luminosity Function from $zsim6$ to $zsim14$ in COSMOS-Web

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Visual Backbones

Kavli Affiliate: Zhuo Li | First 5 Authors: Lefei Shen, Lefei Shen, , , | Summary: Recent studies have revealed that vision models pre-trained on images can perform well in time series forecasting by reformulating forecasting as an image reconstruction task, suggesting their potential as universal time series foundation models. However, effective cross-modal transfer from […]


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