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researcher

Steve Dai

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AR1
  • cs.LG1
  • cs.LO1

identity via Semantic Scholar / OpenAlex

most citedVS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference

13 citations · 15 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AR2021

Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers

Jacob R. Stevens, Rangharajan Venkatesan, Steve Dai +2

Transformers have transformed the field of natural language processing. This performance is largely attributed to the use of stacked self-attention layers, each of which consists o…

cs.LO2021★ 2 cited

Verifying High-Level Latency-Insensitive Designs with Formal Model Checking

Steve Dai, Alicia Klinefelter, Haoxing Ren +4

Latency-insensitive design mitigates increasing interconnect delay and enables productive component reuse in complex digital systems. This design style has been adopted in high-lev…

cs.LG2021★ 13 cited

VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference

Steve Dai, Rangharajan Venkatesan, Haoxing Ren +3

Quantization enables efficient acceleration of deep neural networks by reducing model memory footprint and exploiting low-cost integer math hardware units. Quantization maps floati…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.