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From the 1 of 15 linked papers with an AI index.

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20242026
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cs.LG2026

APPO: Agentic Procedural Policy Optimization

Xucong Wang, Ziyu Ma, Yong Wang +5

Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents. However, most existing metho…

cs.LG2026

PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting

Jiaming Ma, Qihe Huang, Haofeng Ma +6

While existing multivariate time series forecasting models have advanced significantly in modeling periodicity, they largely neglect the periodic heterogeneity common in real-world…

cs.LG2026

FaLW: A Forgetting-aware Loss Reweighting for Long-tailed Unlearning

Liheng Yu, Zhe Zhao, Yuxuan Wang +4

Machine unlearning, which aims to efficiently remove the influence of specific data from trained models, is crucial for upholding data privacy regulations like the ``right to be fo…

cs.LG2026

To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series

Jiaming Ma, Siyuan Mu, Ruilin Tang +6

The prevailing Direct Forecasting (DF) paradigm dominates Long-term Time Series Forecasting (LTSF) by forcing models to predict the entire future horizon in a single forward pass.…

cs.LG2026

A General ReLearner: Empowering Spatiotemporal Prediction by Re-learning Input-label Residual

Jiaming Ma, Binwu Wang, Pengkun Wang +3

Prevailing spatiotemporal prediction models typically operate under a forward (unidirectional) learning paradigm, in which models extract spatiotemporal features from historical ob…

cs.LG2025

Rethinking Crystal Symmetry Prediction: A Decoupled Perspective

Liheng Yu, Zhe Zhao, Xucong Wang +2

Efficiently and accurately determining the symmetry is a crucial step in the structural analysis of crystalline materials. Existing methods usually mindlessly apply deep learning m…