2 papers
cs.CL2025
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
Xiaokang Zhang, Sijia Luo, Bohan Zhang +12
We introduce TableLLM, a robust large language model (LLM) with 8 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embe…
cs.SI2024
Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs
Huanjing Zhao, Beining Yang, Yukuo Cen +6
The text-attributed graph (TAG) is one kind of important real-world graph-structured data with each node associated with raw texts. For TAGs, traditional few-shot node classificati…