papers

Publications (8)

cs.IR2025

Exploiting Inter-Session Information with Frequency-enhanced Dual-Path Networks for Sequential Recommendation

Peng He, Yao Liu, Yanglei Gan +4

Sequential recommendation (SR) aims to predict a user's next item preference by modeling historical interaction sequences. Recent advances often integrate frequency-domain modules…

cs.LG2026

FAiT: Frequency-Aware Inverted Transformer for Multivariate Time Series Forecasting

Peng He, Yao Liu, Yanglei Gan +3

While Transformer-based architectures have established themselves as a dominant paradigm in Multivariate Time Series Forecasting (MTSF), their core self-attention mechanism inheren…

cs.LG2026

Deep Learning-Based Estimation of Ground Reaction Forces in Parkinsonian Gait Using an Optimized Set of IMU Data

Run Lin, Yingtian Tang, Jiawen Xu +6

Accurate gait analysis in Parkinson's disease (PD) typically relies on laboratory-based systems to capture biomechanical data, such as ground reaction forces (GRFs). Estimating GRF…

cs.CL2024

Synergistic Anchored Contrastive Pre-training for Few-Shot Relation Extraction

Da Luo, Yanglei Gan, Rui Hou +4

Few-shot Relation Extraction (FSRE) aims to extract relational facts from a sparse set of labeled corpora. Recent studies have shown promising results in FSRE by employing Pre-trai…

cs.LG2026

Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution Detection

Zhiping Zhou, Xuchen Xie, Yiqiao Qiu +3

This study focuses on incremental learning for image classification, exploring how to reduce catastrophic forgetting of all learned knowledge when access to old data is restricted.…

cs.AI2026

Negative-Aware Diffusion Process for Temporal Knowledge Graph Extrapolation

Yanglei Gan, Peng He, Yuxiang Cai +3

Temporal Knowledge Graph (TKG) reasoning seeks to predict future missing facts from historical evidence. While diffusion models (DM) have recently gained attention for their abilit…