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 […]


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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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Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion

Kavli Affiliate: Jing Wang | First 5 Authors: Wentao Qu, Wentao Qu, , , | Summary: Denoising Diffusion Probabilistic Models (DDPMs) have shown success in robust 3D object detection tasks. Existing methods often rely on the score matching from 3D boxes or pre-trained diffusion priors. However, they typically require multi-step iterations in inference, which limits […]


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DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

Kavli Affiliate: Zhuo Li | First 5 Authors: Haonan Yang, Haonan Yang, , , | Summary: Time Series Forecasting (TSF) faces persistent challenges in modeling intricate temporal dependencies across different scales. Despite recent advances leveraging different decomposition operations and novel architectures based on CNN, MLP or Transformer, existing methods still struggle with static decomposition strategies, […]


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Theoretical Diagnostics for the Physical Conditions in Active Galactic Nuclei under the View of JWST

Kavli Affiliate: Claudio Ricci | First 5 Authors: Lulu Zhang, Lulu Zhang, , , | Summary: With excellent spectral and angular resolutions and, especially, sensitivity, the JWST allows us to observe infrared emission lines that were previously inaccessible or barely accessible. These emission lines are promising for evaluating the physical conditions in different galaxies. Based […]


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Revisiting the Proper Motions of M31 and M33 Using Massive Supergiant Stars with Gaia DR3

Kavli Affiliate: Huawei Zhang | First 5 Authors: Hao Wu, Hao Wu, , , | Summary: The proper motions (PMs) of M31 and M33 are key to understanding the Local Group’s dynamical evolution. However, measurement discrepancies between Gaia blue and red samples, regarding whether the transverse velocity is remarkable, introduce significant ambiguity. In this work, […]


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