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researcher

Maoquan Wang

4 papers here

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

author position
  • middle author4

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

fields
  • cs.SE2
  • cs.CL1
  • cs.PL1

identity via Semantic Scholar / OpenAlex

most citedRethinking the Instruction Quality: LIFT is What You Need

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.PL2024

Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension

Mengnan Qi, Yufan Huang, Yongqiang Yao +3

Large language models (LLMs) has experienced exponential growth, they demonstrate remarkable performance across various tasks. Notwithstanding, contemporary research primarily cent…

cs.CL2023★ 1 cited

Rethinking the Instruction Quality: LIFT is What You Need

Yang Xu, Yongqiang Yao, Yufan Huang +4

Instruction tuning, a specialized technique to enhance large language model (LLM) performance via instruction datasets, relies heavily on the quality of employed data. Existing qua…

cs.SE2023

SUT: Active Defects Probing for Transcompiler Models

Mengnan Qi, Yufan Huang, Maoquan Wang +5

Automatic Program translation has enormous application value and hence has been attracting significant interest from AI researchers. However, we observe that current program transl…

cs.SE2023

Program Translation via Code Distillation

Yufan Huang, Mengnan Qi, Yongqiang Yao +4

Software version migration and program translation are an important and costly part of the lifecycle of large codebases. Traditional machine translation relies on parallel corpora…

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