2 papers
cs.CL2026
Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities
So Hasegawa, Shailaja Keyur Sampat, Lei Liu +1
Current benchmarks for evaluating Large Language Models (LLMs) in data analysis often fail to reflect real-world settings. They typically focus on fact retrieval from small tables…
cs.LG2025
TabGLM: Tabular Graph Language Model for Learning Transferable Representations Through Multi-Modal Consistency Minimization
Anay Majee, Maria Xenochristou, Wei-Peng Chen
Handling heterogeneous data in tabular datasets poses a significant challenge for deep learning models. While attention-based architectures and self-supervised learning have achiev…