2 papers
cs.CL2026
TabRAG: Improving Tabular Document Question Answering for Retrieval Augmented Generation via Structured Representations
Jacob Si, Mike Qu, Michelle Lee +2
Incorporating external knowledge bases in traditional retrieval-augmented generation (RAG) relies on parsing the document, followed by querying a language model with the parsed inf…
cs.LG2025
TabRep: Training Tabular Diffusion Models with a Simple and Effective Continuous Representation
Jacob Si, Zijing Ou, Mike Qu +2
Diffusion models have been the predominant generative model for tabular data generation. However, they face the conundrum of modeling under a separate versus a unified data represe…