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Geon Lee

9 accepted papers

2026

Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and A Simple Remedy

ICML 2026poster

Graph collaborative filtering (GCF) is a dominant paradigm in recommender systems, where contrastive learning (CL) objectives such as the Sampled Softmax (SSM) loss are widely used for optimization. However, it remains unclear how CL interacts with the prediction mechanism of GCF. By unfolding the p…

Cited by 0SourceScholar
2025

RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases

NeurIPS 2025poster

Recent advances have demonstrated the effectiveness of graph-based machine learning on relational databases (RDBs) for predictive tasks. Such approaches require transforming RDBs into graphs, a process we refer to as RDB-to-graph modeling, where rows of tables are represented as nodes and foreign-k…

Cited by 0SourcecodeScholar
2025

TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents

AAAI 2025technical

Time series data is essential in various applications, including climate modeling, healthcare monitoring, and financial analytics. Understanding the contextual information associated with real-world time series data is often essential for accurate and reliable event predictions. In this paper, we in…

2025

TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop

NeurIPS 2025poster

Time series analysis provides essential insights for real-world system dynamics and informs downstream decision-making, yet most existing methods often overlook the rich contextual signals present in auxiliary modalities. To bridge this gap, we introduce TimeXL, a multi-modal prediction framework th…

Cited by 0SourceScholar
2023

Camera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification

ICCV 2023poster

We present a novel unsupervised domain adaption method for person re-identification (reID) that generalizes a model trained on a labeled source domain to an unlabeled target domain. We introduce a camera-driven curriculum learning (CaCL) framework that leverages camera labels of person images to tra…

Cited by 40PDFScholar
2022

Bi-directional Contrastive Learning for Domain Adaptive Semantic Segmentation

ECCV 2022poster

"We present a novel unsupervised domain adaptation method for semantic segmentation that generalizes a model trained with source images and corresponding ground-truth labels to a target domain. A key to domain adaptive semantic segmentation is to learn domain-invariant and discriminative features wi…

Cited by 35SourcePDFScholar
2022

HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams

IJCAI 2022poster

Sequences of group interactions, such as emails, online discussions, and co-authorships, are ubiquitous; and they are naturally represented as a stream of hyperedges (i.e., sets of nodes). Despite its broad potential applications, anomaly detection in hypergraphs (i.e., sets of hyperedges) has rece…

2021

Tendon-Driven Compliant Prosthetic Wrist Consisting of Three Rows Based on the Concept of Tensegrity Structure

RA-L 2021

One degree-of-freedom (DoF) virtual rolling-contact joint for the prosthetic wrist is proposed in this letter. For prosthetic wrists, the wrist mechanism should basically be lightweight and have a wide range of motion (RoM). In addition, it is desirable to have compliant characteristics to protect a

Cited by 20SourceScholar
2021

Video-Based Person Re-Identification With Spatial and Temporal Memory Networks

ICCV 2021poster

Video-based person re-identification (reID) aims to retrieve person videos with the same identity as a query person across multiple cameras. Spatial and temporal distractors in person videos, such as background clutter and partial occlusions over frames, respectively, make this task much more challe…

Cited by 103PDFcodeScholar