Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage. - Isidora Chara Tourni; Lei Guo 017; Taufiq Husada Daryanto; Fabian Zhafransyah; Edward Edberg Halim; Mona Jalal; Boqi Chen; Sha Lai; Hengchang Hu; Margrit Betke; Prakash Ishwar; Derry Tanti Wijaya (EMNLP (Findings), 2021)

KHANQ: A Dataset for Generating Deep Questions in Education. - Huanli Gong; Liangming Pan; Hengchang Hu (COLING, 2022)

PM K-LightGCN: Optimizing for Accuracy and Popularity Match in Course Recommendation. - Yiding Ran; Hengchang Hu; Min-Yen Kan (MORS@RecSys, 2022)

Modeling and Leveraging Prerequisite Context in Recommendation. - Hengchang Hu; Liangming Pan; Yiding Ran; Min-Yen Kan (CoRR, 2022)

Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems. - Hengchang Hu; Wei Guo 006; Yong Liu 020; Min-Yen Kan (CIKM, 2023)

A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommendation Systems. - Chuang Li 006; Hengchang Hu; Yan Zhang 004; Min-Yen Kan; Haizhou Li 001 (KaRS@RecSys, 2023)

Automatic Feature Fairness in Recommendation via Adversaries. - Hengchang Hu; Yiming Cao; Zhankui He; Samson Tan; Min-Yen Kan (SIGIR-AP, 2023)

Do We Really Need Graph Neural Networks for Traffic Forecasting? - Xu Liu 014; Yuxuan Liang; Chao Huang 001; Hengchang Hu; Yushi Cao; Bryan Hooi; Roger Zimmermann (CoRR, 2023)

A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender Systems. - Chuang Li 006; Hengchang Hu; Yan Zhang 004; Min-Yen Kan; Haizhou Li 001 (CoRR, 2023)

Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. - Jiahao Wu 004; Qijiong Liu; Hengchang Hu; Wenqi Fan; Shengcai Liu; Qing Li 001; Xiao-Ming Wu 003; Ke Tang 001 (CoRR, 2023)

Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision. - Hengchang Hu; Qijiong Liu; Chuang Li 006; Min-Yen Kan (ECIR (1), 2024)

Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency. - Xu Liu 014; Yuxuan Liang; Chao Huang 001; Hengchang Hu; Yushi Cao; Bryan Hooi; Roger Zimmermann (ECML/PKDD (3), 2024)

User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation. - Hengchang Hu; Wei Guo 006; Xu Liu 014; Yong Liu 020; Ruiming Tang; Rui Zhang 003; Min-Yen Kan (WSDM, 2024)

Discrete Semantic Tokenization for Deep CTR Prediction. - Qijiong Liu; Hengchang Hu; Jiahao Wu 004; Jieming Zhu; Min-Yen Kan; Xiao-Ming Wu 003 (WWW (Companion Volume), 2024)

Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems. - Chuang Li 006; Yang Deng 002; Hengchang Hu; Min-Yen Kan; Haizhou Li 001 (CoRR, 2024)

Vector Quantization for Recommender Systems: A Review and Outlook. - Qijiong Liu; Xiaoyu Dong; Jiaren Xiao; Nuo Chen 004; Hengchang Hu; Jieming Zhu; Chenxu Zhu; Tetsuya Sakai; Xiao-Ming Wu 003 (CoRR, 2024)

ChatCRS: Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems. - Chuang Li 006; Yang Deng 002; Hengchang Hu; Min-Yen Kan; Haizhou Li 001 (NAACL (Findings), 2025)

Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation. - Jiahao Wu 004; Qijiong Liu; Hengchang Hu; Wenqi Fan; Shengcai Liu; Qing Li 001; Xiao-Ming Wu 003; Ke Tang 001 (WWW (Companion Volume), 2025)

Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders. - Qijiong Liu; Jieming Zhu; Lu Fan; Kun Wang 042; Hengchang Hu; Wei Guo; Yong Liu 018; Xiao-Ming Wu 003 (CoRR, 2025)

CARE: Contextual Adaptation of Recommenders for LLM-based Conversational Recommendation. - Chuang Li 006; Yang Deng 002; Hengchang Hu; See-Kiong Ng; Min-Yen Kan; Haizhou Li 001 (CoRR, 2025)