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GSLB: The Graph Structure Learning Benchmark
Zhixun Li, Liang Wang, Xin Sun +8
Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation g…
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification
Huanhuan Ma, Weizhi Xu, Yifan Wei +4
Fact verification aims to automatically probe the veracity of a claim based on several pieces of evidence. Existing works are always engaging in accuracy improvement, let alone exp…
Uncovering Neural Scaling Laws in Molecular Representation Learning
Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang +5
Molecular Representation Learning (MRL) has emerged as a powerful tool for drug and materials discovery in a variety of tasks such as virtual screening and inverse design. While th…
TCGF: A unified tensorized consensus graph framework for multi-view representation learning
Xiangzhu Meng, Wei Wei, Qiang Liu +2
Multi-view learning techniques have recently gained significant attention in the machine learning domain for their ability to leverage consistency and complementary information acr…
TiBGL: Template-induced Brain Graph Learning for Functional Neuroimaging Analysis
Xiangzhu Meng, Wei Wei, Qiang Liu +2
In recent years, functional magnetic resonance imaging has emerged as a powerful tool for investigating the human brain's functional connectivity networks. Related studies demonstr…
CvFormer: Cross-view transFormers with Pre-training for fMRI Analysis of Human Brain
Xiangzhu Meng, Qiang Liu, Shu Wu +1
In recent years, functional magnetic resonance imaging (fMRI) has been widely utilized to diagnose neurological disease, by exploiting the region of interest (RoI) nodes as well as…
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation
Jinghao Zhang, Qiang Liu, Shu Wu +1
Multimedia content is of predominance in the modern Web era. In real scenarios, multiple modalities reveal different aspects of item attributes and usually possess different import…
Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation
Qiang Liu, Zhaocheng Liu, Zhenxi Zhu +2
Recently, multi-interest models, which extract interests of a user as multiple representation vectors, have shown promising performances for sequential recommendation. However, non…
Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing
Qiang Liu, Junfei Wu, Shu Wu +1
Evidence-aware fake news detection aims to conduct reasoning between news and evidence, which is retrieved based on news content, to find uniformity or inconsistency. However, we f…
Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation
Wenbo Hu, Xin Sun, Qiang liu +2
Post-click conversion rate (CVR) is a reliable indicator of online customers' preferences, making it crucial for developing recommender systems. A major challenge in predicting CVR…
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning
Yuwei Xia, Mengqi Zhang, Qiang Liu +2
Reasoning over Temporal Knowledge Graphs (TKGs) aims to predict future facts based on given history. One of the key challenges for prediction is to learn the evolution of facts. Mo…