35 citations · 59 across the 10 of their papers we have counts for
10 papers
TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models
Xinyi He, Yihao Liu, Mengyu Zhou +5
Tabular data are crucial in many fields and their understanding by large language models (LLMs) under high parameter efficiency paradigm is important. However, directly applying pa…
CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing
Xinyi He, Jiaru Zou, Yun Lin +4
Large Language Models have revolutionized code generation ability by converting natural language descriptions into executable code. However, generating complex code within real-wor…
Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries
Xinyi He, Mengyu Zhou, Xinrun Xu +9
Tabular data analysis is crucial in various fields, and large language models show promise in this area. However, current research mostly focuses on rudimentary tasks like Text2SQL…
TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning
Yuan Sui, Jiaru Zou, Mengyu Zhou +4
Table reasoning tasks have shown remarkable progress with the development of large language models (LLMs), which involve interpreting and drawing conclusions from tabular data base…
Towards Robust Numerical Question Answering: Diagnosing Numerical Capabilities of NLP Systems
Jialiang Xu, Mengyu Zhou, Xinyi He +2
Numerical Question Answering is the task of answering questions that require numerical capabilities. Previous works introduce general adversarial attacks to Numerical Question Answ…
AnaMeta: A Table Understanding Dataset of Field Metadata Knowledge Shared by Multi-dimensional Data Analysis Tasks
Xinyi He, Mengyu Zhou, Mingjie Zhou +7
Tabular data analysis is performed every day across various domains. It requires an accurate understanding of field semantics to correctly operate on table fields and find common p…
ASTA: Learning Analytical Semantics over Tables for Intelligent Data Analysis and Visualization
Lingbo Li, Tianle Li, Xinyi He +3
Intelligent analysis and visualization of tables use techniques to automatically recommend useful knowledge from data, thus freeing users from tedious multi-dimension data mining.…
Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks
Haoyu Dong, Zhoujun Cheng, Xinyi He +6
Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs, and various other document types, a flurry of table pre-training frameworks have been prop…
MultiVision: Designing Analytical Dashboards with Deep Learning Based Recommendation
Aoyu Wu, Yun Wang, Mengyu Zhou +4
We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a…
Table2Charts: Recommending Charts by Learning Shared Table Representations
Mengyu Zhou, Qingtao Li, Xinyi He +7
It is common for people to create different types of charts to explore a multi-dimensional dataset (table). However, to recommend commonly composed charts in real world, one should…