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Jun Sun

8 papers hereh-index 551 citations15 works total

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

author position
  • middle author5
  • last author2

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.AI3
  • cs.SE1
same name
  • Jun Sun — 12 papers, h 3
  • Jun Sun — 8 papers, h 2
  • Jun Sun — 7 papers, h 1
  • Jun Sun — 6 papers, h 3
  • Jun Sun — 6 papers, h 7
  • Jun Sun — 4 papers, h 1

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 citedEfficient and Universal Watermarking for LLM-Generated Code Detection

2 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2026★ 2 cited

Efficient and Universal Watermarking for LLM-Generated Code Detection

Boquan Li, Zirui Fu, Mengdi Zhang +3

Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and…

cs.CR2026

ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection

Wei Zhao, Zhe Li, Peixin Zhang +1

Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet remain vulnerable to indirect pro…

cs.CR2026

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems

Yihao Zhang, Kai Wang, Jiangrong Wu +7

Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constraints and generate unethical or u…

cs.CR2025

Rounding-Guided Backdoor Injection in Deep Learning Model Quantization

Xiangxiang Chen, Peixin Zhang, Jun Sun +2

Model quantization is a popular technique for deploying deep learning models on resource-constrained environments. However, it may also introduce previously overlooked security ris…

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