A survey of graph neural networks for recommender systems: Challenges, methods, and directions

C Gao, Y Zheng, N Li, Y Li, Y Qin, J Piao… - ACM Transactions on …, 2023 - dl.acm.org
Recommender system is one of the most important information services on today's Internet.
Recently, graph neural networks have become the new state-of-the-art approach to …

Proactive conversational agents in the post-chatgpt world

L Liao, GH Yang, C Shah - Proceedings of the 46th International ACM …, 2023 - dl.acm.org
ChatGPT and similar large language model (LLM) based conversational agents have
brought shock waves to the research world. Although astonished by their human-like …

Generalized graph prompt: Toward a unification of pre-training and downstream tasks on graphs

X Yu, Z Liu, Y Fang, Z Liu, S Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Graphs can model complex relationships between objects, enabling a myriad of Web
applications such as online page/article classification and social recommendation. While …

Broadening the view: Demonstration-augmented prompt learning for conversational recommendation

H Dao, Y Deng, DD Le, L Liao - … of the 47th International ACM SIGIR …, 2024 - dl.acm.org
Conversational Recommender Systems (CRSs) leverage natural language dialogues to
provide tailored recommendations. Traditional methods in this field primarily focus on …

User-centric conversational recommendation: Adapting the need of user with large language models

G Zhang - Proceedings of the 17th ACM Conference on …, 2023 - dl.acm.org
Conversational recommender systems (CRS) promise to provide a more natural user
experience for exploring and discovering items of interest through ongoing conversation …

Proactive conversational agents

L Liao, GH Yang, C Shah - … Conference on Web Search and Data …, 2023 - dl.acm.org
Conversational agents, or commonly known as dialogue systems, have gained escalating
popularity in recent years. Their widespread applications support conversational interactions …

Ranking-based contrastive loss for recommendation systems

H Tang, G Zhao, Y He, Y Wu, X Qian - Knowledge-Based Systems, 2023 - Elsevier
The recommendation system is fundamental technology of the internet industry intended to
solve the information overload problem in the big data era. Top-k recommendation is an …

On the Feasibility of Simple Transformer for Dynamic Graph Modeling

Y Wu, Y Fang, L Liao - Proceedings of the ACM on Web Conference …, 2024 - dl.acm.org
Dynamic graph modeling is crucial for understanding complex structures in web graphs,
spanning applications in social networks, recommender systems, and more. Most existing …

Enhancing human-like multimodal reasoning: a new challenging dataset and comprehensive framework

J Wei, C Tan, Z Gao, L Sun, S Li, B Yu, R Guo… - Neural Computing and …, 2024 - Springer
Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems
that exhibit human-like intelligence, especially when tackling complex tasks. While the chain …

Reflecting on experiences for response generation

C Ye, L Liao, S Liu, TS Chua - Proceedings of the 30th ACM International …, 2022 - dl.acm.org
Multimodal dialogue systems attract much attention recently, but they are far from skills like:
1) automatically generate context-specific responses instead of safe but general responses; …