39 citations · 47 across the 6 of their papers we have counts for
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cs.LG2023
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
Ranggi Hwang, Jianyu Wei, Shijie Cao +4
Large language models (LLMs) based on transformers have made significant strides in recent years, the success of which is driven by scaling up their model size. Despite their high…
cs.LG2023★ 5 cited
Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
Yijia Zhang, Lingran Zhao, Shijie Cao +6
Efficient deployment of large language models (LLMs) necessitates low-bit quantization to minimize model size and inference cost. While low-bit integer formats (e.g., INT8/INT4) ha…
cs.LG2021★ 39 cited
WRENCH: A Comprehensive Benchmark for Weak Supervision
Jieyu Zhang, Yue Yu, Yinghao Li +4
Recent Weak Supervision (WS) approaches have had widespread success in easing the bottleneck of labeling training data for machine learning by synthesizing labels from multiple pot…