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Minlong Peng

14 papers hereh-index 171.5k citations35 works total

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

author position
  • first author6
  • middle author8

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.CR2
  • cs.LG2
same name
  • Minlong Peng — 10 papers, h 4
  • Minlong Peng — 4 papers, h 2
  • Minlong Peng — 2 papers, h 1
  • Minlong Peng — 1 paper

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

activity
20182023
most citedHow Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks

36 citations · 74 across the 14 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CL2023★ 4 cited

DocTER: Evaluating Document-based Knowledge Editing

Suhang Wu, Ante Wang, Minlong Peng +4

Knowledge editing aims to correct outdated or inaccurate knowledge in neural networks. In this paper, we explore knowledge editing using easily accessible documents instead of manu…

cs.CL2023

Actively Supervised Clustering for Open Relation Extraction

Jun Zhao, Yongxin Zhang, Qi Zhang +4

Current clustering-based Open Relation Extraction (OpenRE) methods usually adopt a two-stage pipeline. The first stage simultaneously learns relation representations and assignment…

cs.CL2023★ 1 cited

RE-Matching: A Fine-Grained Semantic Matching Method for Zero-Shot Relation Extraction

Jun Zhao, Wenyu Zhan, Xin Zhao +6

Semantic matching is a mainstream paradigm of zero-shot relation extraction, which matches a given input with a corresponding label description. The entities in the input should ex…

cs.CL2023★ 36 cited

How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks

Xuanting Chen, Junjie Ye, Can Zu +7

The GPT-3.5 models have demonstrated impressive performance in various Natural Language Processing (NLP) tasks, showcasing their strong understanding and reasoning capabilities. Ho…

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