activity
20242026
collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting

Jinjin Chi, Lei Feng, Lulu Zhang +6

Time series foundation models (TSFMs) have recently achieved strong zero-shot forecasting performance through large-scale pretraining and retrieval-augmented prediction. However, o…

cs.LG2026

Generalizing Dynamics Modeling More Easily from Representation Perspective

Yiming Wang, Zhengnan Zhang, Genghe Zhang +7

Learning system dynamics from observations is a critical problem in many applications over various real-world complex systems, e.g., climate, ecology, and fluid systems. Recently,…

cs.LG2026

Learning from Label Proportions with Dual-proportion Constraints

Tianhao Ma, Ximing Li, Changchun Li +1

Learning from Label Proportions (LLP) is a weakly supervised problem in which the training data comprise bags, that is, groups of instances, each annotated only with bag-level clas…

cs.LG2026

Semi-Supervised Learning with Balanced Deep Representation Distributions

Changchun Li, Ximing Li, Bingjie Zhang +2

Semi-Supervised Text Classification (SSTC) mainly works under the spirit of self-training. They initialize the deep classifier by training over labeled texts; and then alternativel…

cs.LG2026

Harmful Visual Content Manipulation Matters in Misinformation Detection Under Multimedia Scenarios

Bing Wang, Ximing Li, Changchun Li +4

Nowadays, the widespread dissemination of misinformation across numerous social media platforms has led to severe negative effects on society. To address this challenge, the automa…