Kanghoon Yoon

According to our database, Kanghoon Yoon authored at least 24 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents.

Yeonjun In, Wonjoong Kim, Sangwu Park, Kanghoon Yoon, Chanyoung Park

CoRR, May, 2026

Self-EvolveRec: Self-Evolving Recommender Systems with LLM-based Directional Feedback.

Sein Kim, Sangwu Park, Hongseok Kang, Wonjoong Kim, Jimin Seo, Yeonjun In, Kanghoon Yoon, Chanyoung Park

CoRR, February, 2026

2025

SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification.

Kanghoon Yoon, Minsub Kim, Sungjae Lee, Joonhyung Lee, Sunghyeon Woo, Yeonjun In, Se Jung Kwon, Chanyoung Park, Dongsoo Lee

CoRR, October, 2025

Image is All You Need: Towards Efficient and Effective Large Language Model-Based Recommender Systems.

Kibum Kim, Sein Kim, Hongseok Kang, Jiwan Kim, Heewoong Noh, Yeonjun In, Kanghoon Yoon, Jinoh Oh, Chanyoung Park

CoRR, March, 2025

Weakly Supervised Video Scene Graph Generation via Natural Language Supervision.

Kibum Kim, Kanghoon Yoon, Yeonjun In, Jaehyeong Jeon, Jinyoung Moon, Donghyun Kim, Chanyoung Park

CoRR, February, 2025

Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models.

Yeonjun In, Wonjoong Kim, Kanghoon Yoon, Sungchul Kim, Md. Mehrab Tanjim, Kibum Kim, Chanyoung Park

CoRR, February, 2025

Revisiting Fake News Detection: Towards Temporality-aware Evaluation by Leveraging Engagement Earliness.

Junghoon Kim, Junmo Lee, Yeonjun In, Kanghoon Yoon, Chanyoung Park

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

Training Robust Graph Neural Networks by Modeling Noise Dependencies.

Yeonjun In, Kanghoon Yoon, Sukwon Yun, Kibum Kim, Sungchul Kim, Chanyoung Park

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Weakly Supervised Video Scene Graph Generation via Natural Language Supervision.

Kibum Kim, Kanghoon Yoon, Yeonjun In, Jaehyeong Jeon, Jinyoung Moon, Donghyun Kim, Chanyoung Park

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models.

Yeonjun In, Wonjoong Kim, Kanghoon Yoon, Sungchul Kim, Mehrab Tanjim, Sangwu Park, Kibum Kim, Chanyoung Park

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning.

Kanghoon Yoon, Kibum Kim, Jaehyeong Jeon, Yeonjun In, Donghyun Kim, Chanyoung Park

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning.

Kanghoon Yoon, Kibum Kim, Jaehyung Jeon, Yeonjun In, Donghyun Kim, Chanyoung Park

CoRR, 2024

Self-Guided Robust Graph Structure Refinement.

Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park

Proceedings of the ACM on Web Conference 2024, 2024

Adaptive Self-training Framework for Fine-grained Scene Graph Generation.

Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Semantic Diversity-Aware Prototype-Based Learning for Unbiased Scene Graph Generation.

Jaehyeong Jeon, Kibum Kim, Kanghoon Yoon, Chanyoung Park

Proceedings of the Computer Vision - ECCV 2024, 2024

LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation.

Kibum Kim, Kanghoon Yoon, Jaehyeong Jeon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Debiased Graph Poisoning Attack via Contrastive Surrogate Objective.

Kanghoon Yoon, Yeonjun In, Namkyeong Lee, Kibum Kim, Chanyoung Park

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

LLM4SGG: Large Language Model for Weakly Supervised Scene Graph Generation.

Kibum Kim, Kanghoon Yoon, Jaehyeong Jeon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park

CoRR, 2023

Learning Multivariate Hawkes Process via Graph Recurrent Neural Network.

Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Shift-Robust Molecular Relational Learning with Causal Substructure.

Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Similarity Preserving Adversarial Graph Contrastive Learning.

Yeonjun In, Kanghoon Yoon, Chanyoung Park

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Class Label-aware Graph Anomaly Detection.

Junghoon Kim, Yeonjun In, Kanghoon Yoon, Junmo Lee, Chanyoung Park

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Unbiased Heterogeneous Scene Graph Generation with Relation-Aware Message Passing Neural Network.

Kanghoon Yoon, Kibum Kim, Jinyoung Moon, Chanyoung Park

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

LTE4G: Long-Tail Experts for Graph Neural Networks.

Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022