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Zeyuan Chen

4 papers hereh-index 6910 citations10 works total

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

author position
  • first author2
  • middle author2

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

fields
  • cs.AI1
  • cs.CL1
  • cs.CR1
  • cs.CY1
ORCID 0009-0008-4504-7108
same name
  • Zeyuan Chen — 17 papers, h 10
  • Zeyuan Chen — 12 papers, h 6
  • Zeyuan Chen — 6 papers, h 15
  • Zeyuan Chen — 5 papers, h 3
  • Zeyuan Chen — 4 papers, h 3
  • Zeyuan Chen — 3 papers, h 2

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 citedComprehensive Assessment of Toxicity in ChatGPT

5 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2026

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality

Zeyuan Chen, Ziqing Yang, Yihan Ma +2

As academic submissions grow, the traditional peer review process struggles to keep up, raising concerns about quality and fairness. A trend of using large language models (LLMs) f…

cs.CR2026

Real Money, Fake Models: Deceptive Model Claims in Shadow APIs

Yage Zhang, Yukun Jiang, Zeyuan Chen +3

Access to frontier large language models (LLMs), such as GPT-5 and Gemini-2.5, is often hindered by high pricing, payment barriers, and regional restrictions. These limitations dri…

cs.AI2026

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation

Zeyu Chen, Huanjin Yao, Ziwang Zhao +1

Using Multimodal Large Language Models (MLLMs) as judges to achieve precise and consistent evaluations has gradually become an emerging paradigm across various domains. Evaluating…

cs.CY2023★ 5 cited

Comprehensive Assessment of Toxicity in ChatGPT

Boyang Zhang, Xinyue Shen, Wai Man Si +6

Moderating offensive, hateful, and toxic language has always been an important but challenging topic in the domain of safe use in NLP. The emerging large language models (LLMs), su…

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