46 citations · 48 across the 19 of their papers we have counts for
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cs.AI2026
BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE
Juntong Wu, Jialiang Cheng, Qishen Yin +5
Mixture-of-Experts (MoE) architectures enhance the efficiency of large language models by activating only a subset of experts per token. However, standard MoE employs a fixed Top-K…
cs.AI2024★ 1 cited
SlimGPT: Layer-wise Structured Pruning for Large Language Models
Gui Ling, Ziyang Wang, Yuliang Yan +1
Large language models (LLMs) have garnered significant attention for their remarkable capabilities across various domains, whose vast parameter scales present challenges for practi…
cs.AI2024★ 46 cited
ChemLLM: A Chemical Large Language Model
Di Zhang, Wei Liu, Qian Tan +12
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges a…