2 papers
cs.CL2025
Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity
Yehui Tang, Xiaosong Li, Fangcheng Liu +19
The surgence of Mixture of Experts (MoE) in Large Language Models promises a small price of execution cost for a much larger model parameter count and learning capacity, because on…
cs.CL2024
CFinBench: A Comprehensive Chinese Financial Benchmark for Large Language Models
Ying Nie, Binwei Yan, Tianyu Guo +9
Large language models (LLMs) have achieved remarkable performance on various NLP tasks, yet their potential in more challenging and domain-specific task, such as finance, has not b…