Two papers accepted by ACL 2026!
Two papers from our team were accepted by ACL 2026, including one main-conference paper and one Findings paper. The works improve the efficiency of mixture-of-experts inference and full-parameter LLM fine-tuning.
Reference
- Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
Baihui Liu, Kaiyuan Tian, Wei Wang, Zhaoning Zhang, Linbo Qiao, Dongsheng Li.
The 64th Annual Meeting of the Association for Computational Linguistics (ACL). 2026 - GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning
Kaiyuan Tian, Yu Tang, Gongqingjian Jiang, Baihui Liu, Yifu Gao, Xialin Su, Linbo Qiao, Dongsheng Li.
Findings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL Findings). 2026