most citedMulti-domain Recommendation with Embedding Disentangling and Domain Alignment

29 citations · 62 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2024

Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

Jinyang Li, Nan Huo, Yan Gao +7

Interactive Data Analysis, the collaboration between humans and LLM agents, enables real-time data exploration for informed decision-making. The challenges and costs of collecting…

cs.IR202426 cited

Debiasing Recommendation with Personal Popularity

Wentao Ning, Reynold Cheng, Xiao Yan +4

Global popularity (GP) bias is the phenomenon that popular items are recommended much more frequently than they should be, which goes against the goal of providing personalized rec…

cs.DB2023

Spatio-temporal flow patterns

Chrysanthi Kosyfaki, Nikos Mamoulis, Reynold Cheng +1

Transportation companies and organizations routinely collect huge volumes of passenger transportation data. By aggregating these data (e.g., counting the number of passengers going…

cs.IR202329 cited

Multi-domain Recommendation with Embedding Disentangling and Domain Alignment

Wentao Ning, Xiao Yan, Weiwen Liu +3

Multi-domain recommendation (MDR) aims to provide recommendations for different domains (e.g., types of products) with overlapping users/items and is common for platforms such as A…

cs.CL20237 cited

Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing

Jinyang Li, Binyuan Hui, Reynold Cheng +7

The task of text-to-SQL parsing, which aims at converting natural language questions into executable SQL queries, has garnered increasing attention in recent years, as it can assis…