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researcher

Yi Liu

4 papers hereh-index 5174 citations5 works total

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

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.SE1
  • eess.IV1
same name
  • Yi Liu — 41 papers, h 1
  • Yi Liu — 37 papers, h 21
  • Yi Liu — 26 papers, h 11
  • Yi Liu — 25 papers, h 20
  • Yi Liu — 25 papers
  • Yi Liu — 22 papers, h 11

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedAn Ultra-low Power TinyML System for Real-time Visual Processing at Edge

40 citations · 76 across the 4 of their papers we have counts for

collaborators

4 papers

cs.SE2023★ 34 cited

Automatic Code Summarization via ChatGPT: How Far Are We?

Weisong Sun, Chunrong Fang, Yudu You +10

To support software developers in understanding and maintaining programs, various automatic code summarization techniques have been proposed to generate a concise natural language…

cs.CL2022★ 2 cited

FAST: Improving Controllability for Text Generation with Feedback Aware Self-Training

Junyi Chai, Reid Pryzant, Victor Ye Dong +3

Controllable text generation systems often leverage control codes to direct various properties of the output like style and length. Inspired by recent work on causal inference for…

cs.CL2022

DeepGen: Diverse Search Ad Generation and Real-Time Customization

Konstantin Golobokov, Junyi Chai, Victor Ye Dong +5

We present DeepGen, a system deployed at web scale for automatically creating sponsored search advertisements (ads) for BingAds customers. We leverage state-of-the-art natural lang…

eess.IV2022★ 40 cited

An Ultra-low Power TinyML System for Real-time Visual Processing at Edge

Kunran Xu, Huawei Zhang, Yishi Li +3

Tiny machine learning (TinyML), executing AI workloads on resource and power strictly restricted systems, is an important and challenging topic. This brief firstly presents an extr…

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