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From the 1 of 43 linked papers with an AI index.

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20242026
most citedCATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching

1 citations · 1 across the 3 of their papers we have counts for

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43 papers

cs.LG2026

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework

Tianen Shen, Zhengyu Li, Yutong Li +4

The paper introduces WrapFlow, a framework that directly tokenizes irregular multivariate time‑series observations into continuous‑time tokens and uses a Transformer with a simulat…

cs.LG20261 cited

CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching

Xingjian Wu, Xiangfei Qiu, Zhengyu Li +5

Anomaly detection in multivariate time series is challenging as heterogeneous subsequence anomalies may occur. Reconstruction-based methods, which focus on learning normal patterns…

cs.CV2026

One Layer's Trash is Another Layer's Treasure: Adaptive Layer-wise Visual Token Selection in LVLMs

Yongru Chen, Kai Zhang, Zeliang Zong +4

Large Vision-Language Models (LVLMs) have achieved remarkable success across diverse multimodal tasks, yet their practical deployment remains constrained by the computational burde…

cond-mat.mtrl-sci2026

Inverse Design of Amorphous Materials with Targeted Properties

Jonas A. Finkler, Yan Lin, Tao Du +2

Disordered (amorphous) materials, such as glasses, are emerging as promising candidates for applications within energy storage, nonlinear optics, and catalysis. Their lack of long-…

stat.ML2026

HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation

Hongfan Gao, Wangmeng Shen, Bin Yang +1

Diffusion models have demonstrated strong performance in time series modeling due to their ability to progressively capture complex data distributions through iterative denoising.…

cs.LG2026

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

Xingjian Wu, Junkai Lu, Siyu Yan +4

Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existing MAS typically rely on pre…