Publications (13)
Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey
Liangwei Nathan Zheng, Wei Emma Zhang, Olaf Maennel +2
Mixture-of-Experts (MoE) presents a naturally compatible and scalable framework for multimodal learning, demonstrating strong adaptability across diverse modalities and tasks. Desp…
Devil in the Tail: A Multi-Modal Framework for Drug-Drug Interaction Prediction in Long Tail Distinction
Liangwei Nathan Zheng, Chang George Dong, Wei Emma Zhang +3
Drug-drug interaction (DDI) identification is a crucial aspect of pharmacology research. There are many DDI types (hundreds), and they are not evenly distributed with equal chance…
AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation
Zechao Sun, Shuying Piao, Haolin Jin +4
Class Incremental Semantic Segmentation (CISS) aims to mitigate catastrophic forgetting by maintaining a balance between previously learned and newly introduced knowledge. Existing…
PostHoc FREE Calibrating on Kolmogorov Arnold Networks
Wenhao Liang, Wei Emma Zhang, Lin Yue +3
Kolmogorov Arnold Networks (KANs) are neural architectures inspired by the Kolmogorov Arnold representation theorem that leverage B Spline parameterizations for flexible, locally a…
Calibration Attention: Learning Reliability-Aware Representations for Vision Transformers
Wenhao Liang, Wei Emma Zhang, Lin Yue +4
Most calibration methods operate at the logit level, implicitly assuming that miscalibration can be corrected without changing the underlying representation. We challenge this assu…
What Transfers Under Source Shift? Definitions, Examples, and Fine-Tuning for Climate Disclosure Classification
Guosheng Li, Fenghui Ren, Bin Liu +5
Climate disclosure classification is a fundamental task for analysing corporate climate disclosures, yet such disclosures appear in many different sources -- annual reports, press…