6 papers
Table as a Modality for Large Language Models
Liyao Li, Chao Ye, Wentao Ye +9
To migrate the remarkable successes of Large Language Models (LLMs), the community has made numerous efforts to generalize them to the table reasoning tasks for the widely deployed…
Chinese ModernBERT with Whole-Word Masking
Zeyu Zhao, Ningtao Wang, Xing Fu +1
Encoder-only Transformers have advanced along three axes -- architecture, data, and systems -- yielding Pareto gains in accuracy, speed, and memory efficiency. Yet these improvemen…
ALPS: Attention Localization and Pruning Strategy for Efficient Alignment of Large Language Models
Hao Chen, Haoze Li, Zhiqing Xiao +6
Aligning general-purpose large language models (LLMs) to downstream tasks often incurs significant training adjustment costs. Prior research has explored various avenues to enhance…
Do Two AI Scientists Agree?
Xinghong Fu, Ziming Liu, Max Tegmark
When two AI models are trained on the same scientific task, do they learn the same theory or two different theories? Throughout history of science, we have witnessed the rise and f…
AIGT: AI Generative Table Based on Prompt
Mingming Zhang, Zhiqing Xiao, Guoshan Lu +5
Tabular data, which accounts for over 80% of enterprise data assets, is vital in various fields. With growing concerns about privacy protection and data-sharing restrictions, gener…
Financial Fine-tuning a Large Time Series Model
Xinghong Fu, Masanori Hirano, Kentaro Imajo
Large models have shown unprecedented capabilities in natural language processing, image generation, and most recently, time series forecasting. This leads us to ask the question:…