This page is an archive for papers reviewed by members of the Network Science Lab, along with corresponding presentation materials, as part of the NS-CUK Weekly Seminar series. Launched in Fall 2022, this seminar series is intended to be a platform for the members of the Network Science Lab at the Catholic University of Korea to exchange insights and understanding of state-of-the-art AI methodologies and models for graph mining.
Previous Years
2025
Apr 14th, 2025
V.T. Hoang, Review on "Few-Shot Graph Learning for Molecular Property Prediction", WWW 2021
T.B.T. Do, Review on "Geometry Sensitive Cross-Modal Reasoning for Composed Query Based Image Retrieval", IEEE Transactions on Image Processing, 2022
J.H. Shim, Review on "SPECTER: Document-level Representation Learning using Citation-informed Transformers", ACL 2020
Apr 07th, 2025
V.T. Hoang, Review on "Graph Sampling-based Meta-Learning for Molecular Property Prediction", IJCAI 2023
T.B.T. Do, Review on "Joint Attribute Manipulation and Modality Alignment Learning for Composing Text and Image to Image Retrieval", ACM MM 2020
J.W. Jeong, Review on "Property-Aware Relation Networks for Few-Shot Molecular Property Prediction", NeurIPS 2021
H.W. Kim, Review on "CoLAKE: Contextualized Language and Knowledge Embedding", COLING 2020
Mar 31st, 2025
V.T. Hoang, Review on "Higher Order Structures For Graph Explanations", AAAI 2025
T.B.T. Do, Review on "Graph Transformer GANs for Graph-Constrained House Generation", CVPR 2023
J.H. Shim, Review on "A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks", Scientometrics, 2020
J.H. Cho, Review on "How Powerful are Graph Neural Networks?", ICLR 2019
Mar 24th, 2025
V.T. Hoang, Review on "3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation", AAAI 2025
T.B.T. Do, Review on "Post-OCR Paragraph Recognition by Graph Convolutional Networks", WACV 2022
H.W. Kim, Review on "Coarformer: Transformer for large graph via graph coarsening", OpenReview Preprint, 2022
Mar 17th, 2025
V.T. Hoang, Review on "GLAD: Improving Latent Graph Generative Modeling with Simple Quantization", AAAI 2025
T.B.T. Do, Review on "DriveLM: Driving with Graph Visual Question Answering", ECCV 2024
J.W. Jeong, Review on "KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction", KDD 2022
Mar 10th, 2025
V.T. Hoang, Review on "MORE: Molecule Pretraining with Multi-Level Pretext Task", AAAI 2025
T.B.T. Do, Review on "WiGNet: Windowed Vision Graph Neural Network", WACV 2025
J.H. Shim, Review on "CASER : Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding", WSDM 2018
J.H. Cho, Review on "Translating Embeddings for Modeling Multi-relational Data", NeurIPS 2013
Mar 03rd, 2025
T.B.T. Do, Review on "Autoregressive Adaptive Hypergraph Transformer for Skeleton-based Activity Recognition", WACV 2025
J.W. Jeong, Review on "Self-Supervised Graph Transformer on Large-Scale Molecular Data", NeurIPS 2020
H.W. Kim, Review on "Towards Foundation Models for Knowledge Graph Reasoning", ICLR 2024
Feb 24th, 2025
V.T. Hoang, Review on "Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations", AAAI 2025
T.B.T. Do, Review on "GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph", NeurIPS 2023
J.H. Cho, Review on "Graph Attention Networks", ICLR 2018
Feb 17th, 2025
V.T. Hoang, Review on "MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction", IJCAI 2024
T.B.T. Do, Review on "HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding", COLING 2025
J.W. Jeong, Review on "Keep It Simple: Towards Accurate Vulnerability Detection for Large Code Graphs", arXiv preprint arXiv:2412.10164 2024
Feb 10th, 2025
V.T. Hoang, Review on "MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning", WSDM 2024
T.B.T. Do, Review on "Multiscale Graph Texture Network", ECCV 2024
Feb 03rd, 2025
T.B.T. Do, Review on "Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection", AAAI 2025
J.H. Shim, Review on "BERT4Rec : Sequential Recommendation with Bidirectional Encoder Representations from Transformer", CIKM 2019
H.W. Kim, Review on "STEM: Unleashing the Power of Embeddings for Multi-Task Recommendation", AAAI 2024
J.H. Cho, Review on "Asymmetric Transitivity Preserving Graph Embedding", KDD 2016
Jan 20th, 2025
V.T. Hoang, Review on "Multi-channel learning for integrating structural hierarchies into contextdependent molecular representation", Nature Communications 2025
T.B.T. Do, Review on "HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimation", ECCV 2024
Jan 13th, 2025
V.T. Hoang, Review on "On the Scalability of GNNs for Molecular Graphs ", NeurIPS 2024
T.B.T. Do, Review on "Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification", AAAI 2025
J.H. Shim, Review on "An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention", AAAI 2024
H.W. Kim, Review on "Progressive layered extraction (PLE): A novel multi-task learning (MTL) model for personalized recommendations", Conference on Recommender Systems 2020
Jan 6th, 2025
V.T. Hoang, Review on "Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules", ICLR 2023
T.B.T. Do, Review on "SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation", AAAI 2025
J.W. Jeong, Review on "SchNet: A continuous-filter convolutional neural network for modeling quantum interactions", NeurIPS 2017
