Papers by Xiaoqian Jiang

2 papers
Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing (2020.lrec-1)

Copied to clipboard

Challenge: Clinical trials require that patients meet eligibility criteria to ensure safety and effectiveness of studies.
Approach: They propose a dataset that includes the first-of-its-kind eligibility-criteria corpus and queries for criteria-to-sql . they propose 'neuro semantic parser' which can translate eligibility criteria to executable SQL queries .
Outcome: The proposed parser outperforms existing state-of-the-art general-purpose models while highlighting the challenges presented by the new dataset.
MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data (2026.findings-acl)

Copied to clipboard

Challenge: Existing models for tabular data generation require large amounts of data to train effectively.
Approach: They propose a framework to generate tabular data powered by large language models that emulates a Generative Adversarial Network.
Outcome: The proposed framework outperforms state-of-the-art models while keeping privacy of real data.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations