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researcher

Peng Wang

4 papers here

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

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
ORCID 0000-0002-5931-8852
same name
  • Peng Wang — 45 papers, h 32
  • Peng Wang — 24 papers, h 19
  • Peng Wang — 20 papers, h 25
  • Peng Wang — 19 papers, h 32
  • Peng Wang — 16 papers, h 16
  • Peng Wang — 14 papers

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 citedQwen Technical Report

110 citations · 172 across the 4 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024★ 60 cited

Qwen2 Technical Report

An Yang, Baosong Yang, Binyuan Hui +59

This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…

cs.CL2023★ 110 cited

Qwen Technical Report

Jinze Bai, Shuai Bai, Yunfei Chu +45

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…

cs.CL2023★ 1 cited

CoT-MoTE: Exploring ConTextual Masked Auto-Encoder Pre-training with Mixture-of-Textual-Experts for Passage Retrieval

Guangyuan Ma, Xing Wu, Peng Wang +1

Passage retrieval aims to retrieve relevant passages from large collections of the open-domain corpus. Contextual Masked Auto-Encoding has been proven effective in representation b…

cs.CL2023★ 1 cited

CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval

Xing Wu, Guangyuan Ma, Peng Wang +4

Growing techniques have been emerging to improve the performance of passage retrieval. As an effective representation bottleneck pretraining technique, the contextual masked auto-e…

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