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Junjie Chen

Hefei University of Technology

12 papers hereh-index 7309 citations17 works total

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

author position
  • first author3
  • middle author9

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL6
  • cs.CV5
  • cs.LG1
affiliations
  • Hefei University of Technology
  • Insititute of Artificial Intelligence, Hefei Comprehensive National Science Center
Homepage
same name
  • Junjie Chen — 56 papers, h 43
  • Junjie Chen — 13 papers, h 18
  • Junjie Chen — 13 papers, h 8
  • Junjie Chen — 11 papers, h 5
  • Junjie Chen — 10 papers, h 11
  • Junjie Chen — 8 papers, h 4

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
20242026
most citedSeeing Sarcasm Through Different Eyes: Analyzing Multimodal Sarcasm Perception in Large Vision-Language Models

3 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2025 · cs.CLShow all

3 papers · 2 filters

cs.CL2025★ 1 cited

TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration

Weiya Li, Junjie Chen, Bei Li +8

Machine translation has long been a central task in natural language processing. With the rapid advancement of large language models (LLMs), there has been remarkable progress in t…

cs.CL2025

Shifting AI Efficiency From Model-Centric to Data-Centric Compression

Xuyang Liu, Zichen Wen, Shaobo Wang +14

The advancement of large language models (LLMs) and multi-modal LLMs (MLLMs) has historically relied on scaling model parameters. However, as hardware limits constrain further mode…

cs.CL2025★ 3 cited

Seeing Sarcasm Through Different Eyes: Analyzing Multimodal Sarcasm Perception in Large Vision-Language Models

Junjie Chen, Xuyang Liu, Subin Huang +2

With the advent of large vision-language models (LVLMs) demonstrating increasingly human-like abilities, a pivotal question emerges: do different LVLMs interpret multimodal sarcasm…

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