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Langming Liu

2 accepted papers

2026

Expert Divergence Learning for MoE-based Language Models

ICLR 2026poster

The Mixture-of-Experts (MoE) architecture is a powerful technique for scaling language models, yet it often suffers from expert homogenization, where experts learn redundant functionalities, thereby limiting MoE's full potential. To address this, we introduce Expert Divergence Learning, a novel pre-…

Cited by 0SourceScholar
2025

How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models

EMNLP 2025

Large language models (LLMs) have attracted significant attention due to their impressive general capabilities across diverse downstream tasks. However, without domain-specific optimization, they often underperform on specialized knowledge benchmarks and even produce hallucination. Recent studies sh

Cited by 0SourcePDFScholar