Hengchang Hu

According to our database, Hengchang Hu authored at least 23 papers between 2021 and 2026.

Collaborative distances:

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

2026

Improving Conversational Recommendation with Contextual Adaptation of External Recommenders and LLM-Based Reranking.

Chuang Li, Weida Liang, Hengchang Hu, See-Kiong Ng, Min-Yen Kan, Haizhou Li, Yang Deng

Proceedings of the Advances in Information Retrieval, 2026

Rethinking Reading Order: Toward Generalizable Document Understanding with LLM-based Relation Modeling.

Weishi Wang, Hengchang Hu, Daniel Dahlmeier

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2025

Document Intelligence in the Era of Large Language Models: A Survey.

Weishi Wang, Hengchang Hu, Zhijie Zhang, Zhaochen Li, Hongxin Shao, Daniel Dahlmeier

CoRR, October, 2025

CARE: Contextual Adaptation of Recommenders for LLM-based Conversational Recommendation.

Chuang Li, Yang Deng, Hengchang Hu, See-Kiong Ng, Min-Yen Kan, Haizhou Li

CoRR, August, 2025

Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders.

Qijiong Liu, Jieming Zhu, Lu Fan, Kun Wang, Hengchang Hu, Wei Guo, Yong Liu, Xiao-Ming Wu

CoRR, March, 2025

Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation.

Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

ChatCRS: Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems.

Chuang Li, Yang Deng, Hengchang Hu, Min-Yen Kan, Haizhou Li

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

2024

Vector Quantization for Recommender Systems: A Review and Outlook.

Qijiong Liu, Xiaoyu Dong, Jiaren Xiao, Nuo Chen, Hengchang Hu, Jieming Zhu, Chenxu Zhu, Tetsuya Sakai, Xiao-Ming Wu

CoRR, 2024

Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems.

Chuang Li, Yang Deng, Hengchang Hu, Min-Yen Kan, Haizhou Li

CoRR, 2024

Discrete Semantic Tokenization for Deep CTR Prediction.

Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation.

Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency.

Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision.

Hengchang Hu, Qijiong Liu, Chuang Li, Min-Yen Kan

Proceedings of the Advances in Information Retrieval, 2024

2023

Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation.

Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang

CoRR, 2023

A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems.

Chuang Li, Hengchang Hu, Yan Zhang, Min-Yen Kan, Haizhou Li

CoRR, 2023

Do We Really Need Graph Neural Networks for Traffic Forecasting?

Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

CoRR, 2023

Automatic Feature Fairness in Recommendation via Adversaries.

Hengchang Hu, Yiming Cao, Zhankui He, Samson Tan, Min-Yen Kan

Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2023

A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommendation Systems.

Chuang Li, Hengchang Hu, Yan Zhang, Min-Yen Kan, Haizhou Li

Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems.

Hengchang Hu, Wei Guo, Yong Liu, Min-Yen Kan

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

2022

Modeling and Leveraging Prerequisite Context in Recommendation.

Hengchang Hu, Liangming Pan, Yiding Ran, Min-Yen Kan

CoRR, 2022

PM K-LightGCN: Optimizing for Accuracy and Popularity Match in Course Recommendation.

Yiding Ran, Hengchang Hu, Min-Yen Kan

Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

KHANQ: A Dataset for Generating Deep Questions in Education.

Huanli Gong, Liangming Pan, Hengchang Hu

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage.

Isidora Chara Tourni, Lei Guo, Taufiq Husada Daryanto, Fabian Zhafransyah, Edward Edberg Halim, Mona Jalal, Boqi Chen, Sha Lai, Hengchang Hu, Margrit Betke, Prakash Ishwar, Derry Tanti Wijaya

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021