activity
20202026
most citedNeural Interactive Collaborative Filtering

123 citations · 218 across the 11 of their papers we have counts for

collaborators

13 papers

cs.LG2026

QAM: Quadratic-Accurate Checkpoint Merging via Sequential Consistency

Shihao Wang, Rui Kong, Xinran Chen +7

Saved checkpoints record states along a training trajectory, but generally do not determine the updates at states that would be visited under a different schedule. We study how acc…

cs.CL2026

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

Yu Wang, Yuchen Li, Rui Kong +11

Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing routers are effective in si…

cs.IR2026

TextClusterLab: An Integrated Framework for Reliable Text Clustering Studies

Daoming Wan, Yizheng Huang, Jimmy X. Huang

In recent years, text clustering has become a critical technique for applications including intent discovery, topic mining, and recommendation systems. However, evaluating text clu…

cs.IR2024

A Survey on Bundle Recommendation: Methods, Applications, and Challenges

Meng Sun, Lin Li, Ming Li +5

In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by…

cs.CL2024★ 2 cited

A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations

Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari +10

Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough…

cs.IR2024

Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives

Emrul Hasan, Mizanur Rahman, Chen Ding +2

Recommender systems play a pivotal role in helping users navigate an overwhelming selection of products and services. On online platforms, users have the opportunity to share feedb…

cs.IR2024

MealRec: A Meal Recommendation Dataset with Meal-Course Affiliation for Personalization and Healthiness

Ming Li, Lin Li, Xiaohui Tao +1

Meal recommendation, as a typical health-related recommendation task, contains complex relationships between users, courses, and meals. Among them, meal-course affiliation associat…

cs.CL2024

One Subgraph for All: Efficient Reasoning on Opening Subgraphs for Inductive Knowledge Graph Completion

Zhiwen Xie, Yi Zhang, Guangyou Zhou +3

Knowledge Graph Completion (KGC) has garnered massive research interest recently, and most existing methods are designed following a transductive setting where all entities are obs…

cs.IR2024★ 58 cited

A Survey on Retrieval-Augmented Text Generation for Large Language Models

Yizheng Huang, Jimmy Huang

Retrieval-Augmented Generation (RAG) merges retrieval methods with deep learning advancements to address the static limitations of large language models (LLMs) by enabling the dyna…

cs.IR2024★ 1 cited

Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges

Jiajia Wang, Jimmy X. Huang, Xinhui Tu +4

Recent years have witnessed a substantial increase in the use of deep learning to solve various natural language processing (NLP) problems. Early deep learning models were constrai…

cs.IR2024★ 33 cited

Exploring ChatGPT for Next-generation Information Retrieval: Opportunities and Challenges

Yizheng Huang, Jimmy Huang

The rapid advancement of artificial intelligence (AI) has highlighted ChatGPT as a pivotal technology in the field of information retrieval (IR). Distinguished from its predecessor…

cs.CL2023★ 1 cited

A Comprehensive Evaluation of Large Language Models on Benchmark Biomedical Text Processing Tasks

Israt Jahan, Md Tahmid Rahman Laskar, Chun Peng +1

Recently, Large Language Models (LLM) have demonstrated impressive capability to solve a wide range of tasks. However, despite their success across various tasks, no prior work has…

cs.IR2020★ 123 cited

Neural Interactive Collaborative Filtering

Lixin Zou, Long Xia, Yulong Gu +4

In this paper, we study collaborative filtering in an interactive setting, in which the recommender agents iterate between making recommendations and updating the user profile base…