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Yulin Chen

16 papers hereh-index 8305 citations17 works total

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

author position
  • first author5
  • middle author8

Across the 13 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CR12
  • cs.CL4
same name
  • Yulin Chen — 50 papers, h 45
  • Yulin Chen — 18 papers, h 17
  • Yulin Chen — 17 papers, h 7
  • Yulin Chen — 17 papers, h 7
  • Yulin Chen — 12 papers, h 10
  • Yulin Chen — 9 papers, h 6

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
20232026
most citedPrivacy in Large Language Models: Attacks, Defenses and Future Directions

27 citations · 31 across the 15 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance

Haoran Li, Yulin Chen, Huihao Jing +6

Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires reasoning about the context…

cs.CL2025

PrivaCI-Bench: Evaluating Privacy with Contextual Integrity and Legal Compliance

Haoran Li, Wenbin Hu, Huihao Jing +6

Recent advancements in generative large language models (LLMs) have enabled wider applicability, accessibility, and flexibility. However, their reliability and trustworthiness are…

cs.CL2024

Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory

Haoran Li, Wei Fan, Yulin Chen +5

Privacy research has attracted wide attention as individuals worry that their private data can be easily leaked during interactions with smart devices, social platforms, and AI app…

cs.CL2023★ 27 cited

Privacy in Large Language Models: Attacks, Defenses and Future Directions

Haoran Li, Yulin Chen, Jinglong Luo +9

The advancement of large language models (LLMs) has significantly enhanced the ability to effectively tackle various downstream NLP tasks and unify these tasks into generative pipe…

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