167 citations · 189 across the 13 of their papers we have counts for
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cs.CL2026
HLA: Expressive Hybrid Linear Attention via Chunk-Wise Dynamic Mixing
Zhuokun Chen, Xi Lin, Xiyu Wu +3
Linear attention enables efficient long-context autoregressive decoding by compressing history into recurrent states, but this compression can make selective access to sparse and d…
cs.CL2024★ 1 cited
ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models
Jing Liu, Ruihao Gong, Mingyang Zhang +3
LLM development involves pre-training a foundation model on massive data, followed by fine-tuning on task-specific data to create specialized experts. Serving these experts can pos…
cs.CL2023★ 11 cited
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
Jing Liu, Ruihao Gong, Xiuying Wei +3
Large Language Models (LLMs) excel in NLP, but their demands hinder their widespread deployment. While Quantization-Aware Training (QAT) offers a solution, its extensive training c…