Publications (12)
RecGPT: A Foundation Model for Sequential Recommendation
Yangqin Jiang, Xubin Ren, Lianghao Xia +3
This work addresses a fundamental barrier in recommender systems: the inability to generalize across domains without extensive retraining. Traditional ID-based approaches fail enti…
GraphPro: Graph Pre-training and Prompt Learning for Recommendation
Yuhao Yang, Lianghao Xia, Da Luo +2
GNN-based recommenders have excelled in modeling intricate user-item interactions through multi-hop message passing. However, existing methods often overlook the dynamic nature of…
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…
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer
Erxue Min, Yu Rong, Tingyang Xu +6
Click-Through Rate (CTR) prediction, which aims to estimate the probability that a user will click an item, is an essential component of online advertising. Existing methods mainly…
Aspect-oriented Opinion Alignment Network for Aspect-Based Sentiment Classification
Xueyi Liu, Rui Hou, Yanglei Gan +4
Aspect-based sentiment classification is a crucial problem in fine-grained sentiment analysis, which aims to predict the sentiment polarity of the given aspect according to its con…
The Mechanical Behavior of Macroscale Single-crystal Graphene
Anirban Kundu, Seyed Kamal Jalali, Minhyeok Kim +6
Despite extensive microscale studies, the macroscopic mechanical properties of monolayer graphene remain underexplored. Here, we report the Young's modulus ( = 1.11 0.04 T…
Fermi velocity renormalization in graphene probed by terahertz time-domain spectroscopy
Patrick R. Whelan, Qian Shen, Binbin Zhou +13
We demonstrate terahertz time-domain spectroscopy (THz-TDS) to be an accurate, rapid and scalable method to probe the interaction-induced Fermi velocity renormalization νF^* of ch…
Debiased Contrastive Learning for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia +3
Current sequential recommender systems are proposed to tackle the dynamic user preference learning with various neural techniques, such as Transformer and Graph Neural Networks (GN…
RecLM: Recommendation Instruction Tuning
Yangqin Jiang, Yuhao Yang, Lianghao Xia +3
Modern recommender systems aim to deeply understand users' complex preferences through their past interactions. While deep collaborative filtering approaches using Graph Neural Net…
DiffMM: Multi-Modal Diffusion Model for Recommendation
Yangqin Jiang, Lianghao Xia, Wei Wei +3
The rise of online multi-modal sharing platforms like TikTok and YouTube has enabled personalized recommender systems to incorporate multiple modalities (such as visual, textual, a…
Accurate Real Time Localization Tracking in A Clinical Environment using Bluetooth Low Energy and Deep Learning
Zohaib Iqbal, Da Luo, Peter Henry +10
Deep learning has started to revolutionize several different industries, and the applications of these methods in medicine are now becoming more commonplace. This study focuses on…
Degradation of Black Phosphorus (BP): The Role of Oxygen and Water
Yuan Huang, Jingsi Qiao, Kai He +10
Black phosphorus (BP) has attracted significant interest as a monolayer or few-layer material with extraordinary electrical and optoelectronic properties. However, degradation in a…