From the 1 of 22 linked papers with an AI index.
22 papers
Towards Efficient Reasoning in LLM-Based Recommender Systems via Model Merging
Linh Dieu Le, Tong Chen, Shazia Sadiq +3
Large language model-based recommender systems are increasingly adopting slow-thinking models that generate step-by-step reasoning before making predictions, often achieving higher…
GRAFT: Graph-Matched Retrieval and Fusion of Tables in Data Lakes
Daomin Ji, Hui Luo, Zhifeng Bao +2
The paper introduces GRAFT, a system that retrieves and combines tables from large data lakes by matching query intent graphs to a heterogeneous data lake graph and using reinforce…
Alignment-Guided Largest Table Overlap Size Estimation
Ge Lee, Shixun Huang, Zhifeng Bao +2
Fast estimation of the size of the largest overlap between tables enables blocking and query-by-table retrieval in large table repositories. The first and the state-of-the-art esti…
Building AI Companions that Prioritise Learning over Performance
Hassan Khosravi, Dragan Gasevic, Shazia Sadiq +7
Large language models (LLMs) are rapidly transforming knowledge work by improving the quality and efficiency of tasks such as writing, coding, and data analysis. However, their gro…
Unified Data Discovery across Query Modalities and User Intents
Tingting Wang, Shixun Huang, Zhifeng Bao +4
Data discovery - retrieving relevant tables from a data lake in response to user queries - is a fundamental building block for downstream analytics. In practice, data discovery mus…
Self-Distilled Reinforcement Learning for Co-Evolving Agentic Recommender Systems
Zongwei Wang, Min Gao, Hongzhi Yin +5
Large language model-empowered agentic recommender systems (ARS) reformulate recommendation as a multi-turn interaction between a recommender agent and a user agent, enabling itera…