An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems

H Shaik, A Doboli - arxiv preprint arxiv:2501.00562, 2024 - arxiv.org
Large Language Models offer new opportunities to devise automated implementation
generation methods that can tackle problem solving activities beyond traditional methods …

Tqa-bench: Evaluating llms for multi-table question answering with scalable context and symbolic extension

Z Qiu, Y Peng, G He, B Yuan, C Wang - arxiv preprint arxiv:2411.19504, 2024 - arxiv.org
The advent of large language models (LLMs) has unlocked great opportunities in complex
data management tasks, particularly in question answering (QA) over complicated multi …

Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding

D Ji, L Zhu, S Gao, P Xu, H Lu, J Ye, F Zhao - arxiv preprint arxiv …, 2024 - arxiv.org
The ubiquity and value of tables as semi-structured data across various domains necessitate
advanced methods for understanding their complexity and vast amounts of information …

LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation

X He, Y Ban, J Zou, T Wei, CB Cook, J He - arxiv preprint arxiv …, 2024 - arxiv.org
Missing data imputation is a critical challenge in various domains, such as healthcare and
finance, where data completeness is vital for accurate analysis. Large language models …

Table-Critic: A Multi-Agent Framework for Collaborative Criticism and Refinement in Table Reasoning

P Yu, G Chen, J Wang - arxiv preprint arxiv:2502.11799, 2025 - arxiv.org
Despite the remarkable capabilities of large language models (LLMs) in various reasoning
tasks, they still struggle with table reasoning tasks, particularly in maintaining consistency …