16 citations · 17 across the 6 of their papers we have counts for
6 papers
MontePrep: Monte-Carlo-Driven Automatic Data Preparation without Target Data Instances
Congcong Ge, Yachuan Liu, Yixuan Tang +3
In commercial systems, a pervasive requirement for automatic data preparation (ADP) is to transfer relational data from disparate sources to targets with standardized schema specif…
ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models
Yachuan Liu, Xiaochun Wei, Lin Shi +4
Large language models (LLMs) face significant challenges in ex-ante reasoning, where analysis, inference, or predictions must be made without access to information from future even…
Text-to-Pipeline: Bridging Natural Language and Data Preparation Pipelines
Yuhang Ge, Yachuan Liu, Zhangyan Ye +2
Data preparation (DP) transforms raw data into a form suitable for downstream applications, typically by composing operations into executable pipelines. Building such pipelines is…
Position: Towards Bidirectional Human-AI Alignment
Hua Shen, Tiffany Knearem, Reshmi Ghosh +21
Recent advances in general-purpose AI underscore the urgent need to align AI systems with human goals and values. Yet, the lack of a clear, shared understanding of what constitutes…
Meta Semantic Template for Evaluation of Large Language Models
Yachuan Liu, Liang Chen, Jindong Wang +2
Do large language models (LLMs) genuinely understand the semantics of the language, or just memorize the training data? The recent concern on potential data contamination of LLMs h…
Ranking & Reweighting Improves Group Distributional Robustness
Yachuan Liu, Bohan Zhang, Qiaozhu Mei +1
Recent work has shown that standard training via empirical risk minimization (ERM) can produce models that achieve high accuracy on average but low accuracy on underrepresented gro…