46 citations · 48 across the 5 of their papers we have counts for
5 papers · 1 filter
Reward-SQL: Boosting Text-to-SQL via Stepwise Execution-Aware Reasoning and Process-Supervised Rewards
Yuxin Zhang, Meihao Fan, Ju Fan +5
Recent advances in large language models (LLMs) trained with reinforcement learning (RL) have improved Text-to-SQL performance. However, RL-based approaches still struggle with com…
SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graph
Teng Lin, Yizhang Zhu, Yuyu Luo +1
Multi-entity question answering (MEQA) poses significant challenges for large language models (LLMs), which often struggle to consolidate scattered information across multiple docu…
SketchFill: Sketch-Guided Code Generation for Imputing Derived Missing Values
Yunfan Zhang, Changlun Li, Yuyu Luo +1
Missing value is a critical issue in data science, significantly impacting the reliability of analyses and predictions. Missing value imputation (MVI) is a longstanding problem bec…
ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering
Yifan Wu, Lutao Yan, Leixian Shen +3
Chart question answering (ChartQA) tasks play a critical role in interpreting and extracting insights from visualization charts. While recent advancements in multimodal large langu…
Are Large Language Models Good Statisticians?
Yizhang Zhu, Shiyin Du, Boyan Li +2
Large Language Models (LLMs) have demonstrated impressive capabilities across a range of scientific tasks including mathematics, physics, and chemistry. Despite their successes, th…