Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
Demystifying Data Organization for Enhanced LLM Training
Yalun Dai, Yangyu Huang, Tongshen Yang +8
Large Language Models (LLMs) have revolutionized various fields, yet their training efficiency is heavily reliant on effective data curation. While data selection has been widely s…
cs.AI2026
ConMoE: Expert-Pool Consolidation via Prototype Reassignment for MoE Compression
Yilun Yao, Jiaming Pan, Elsie Dai +3
Mixture-of-Experts (MoE) language models reduce per-token computation but still require storing and serving all experts, making deployment memory-intensive. Existing post-training…