8 citations · 10 across the 7 of their papers we have counts for
9 papers
BI-Agent and BI-Bench: Towards Automating End-to-End Business Intelligence
Chuxuan Hu, Yeye He, Penny Zhou +3
Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tableau. In traditional BI workflo…
Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models
Yurong Liu, Yeye He, Haoyu Dong +4
Predicting missing cell values in tabular data is a fundamental problem in data cleaning. While state-of-the-art reasoning models show great promise in predicting missing values in…
Auto-Relate: A Unified Approach to Discovering Reliable Functional Relationships Leveraging Statistical Tests
Ziyan Han, Yeye He, Shuyuan Kang +8
Tables in spreadsheets, computational notebooks, and databases often contain rich inter-column relationships. Yet these relationships are typically implicit and are often lost when…
MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark
Junjie Xing, Yeye He, Mengyu Zhou +6
Tables and table-based use cases play a crucial role in many important real-world applications, such as spreadsheets, databases, and computational notebooks, which traditionally re…
Auto-Prep: Holistic Prediction of Data Preparation Steps for Self-Service Business Intelligence
Eugenie Y. Lai, Yeye He, Surajit Chaudhuri
Business Intelligence (BI) plays a critical role in empowering modern enterprises to make informed data-driven decisions, and has grown into a billion-dollar business. Self-service…
Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables
Qixu Chen, Yeye He, Raymond Chi-Wing Wong +5
Data cleaning is a long-standing challenge in data management. While powerful logic and statistical algorithms have been developed to detect and repair data errors in tables, exist…
Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning
Junjie Xing, Yeye He, Mengyu Zhou +4
Language models such as GPT and Llama have shown remarkable ability on diverse natural language tasks, yet their performance on complex table tasks (e.g., NL-to-Code and data clean…
Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Sibei Chen, Yeye He, Weiwei Cui +5
Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface. Toda…
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Peng Li, Yeye He, Dror Yashar +6
Language models, such as GPT-3.5 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks. However, when probing languag…