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Haijun Wang

9 papers hereh-index 5154 citations25 works total

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

author position
  • middle author7
  • last author1

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CR5
  • cs.SE3
  • cs.AI1
same name
  • Haijun Wang — 6 papers, h 15
  • Haijun Wang — 4 papers, h 8
  • Haijun Wang — 3 papers, h 6
  • Haijun Wang — 1 paper, h 1
  • Haijun Wang — 1 paper, 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

activity
20242026
most citedStrategic Chain-of-Thought: Guiding Accurate Reasoning in LLMs through Strategy Elicitation

5 citations · 6 across the 7 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CR2026

Not All Tokens Are Equal: Region-Aware Consistency Repair of Backdoors in MLLMs

Jiali Wei, Ming Fan, Mingkun Zhang +6

MLLMs are increasingly deployed in user-facing applications, yet they inherit backdoor risks from the pipelines used to construct them: triggers may reside in images, texts, or bot…

cs.CR2026

Tracing the Shadows: Automatic Tracking and Analysis of Crypto Money Laundering via Transaction Semantic Analysis

Hao Wu, Haijun Wang, Shangwang Li +4

With the rapid advancement of decentralized finance (DeFi), security incidents related to cryptocurrency have become increasingly prevalent. After such incidents, attackers typical…

cs.SE2026

TrapHunter: Exposing Covert Pathways in Trap Token Contracts

Yin Wu, Yixuan Liu, Yi Li +5

Standardized token contracts (e.g., ERC-20) form the foundation of digital assets. However, attackers increasingly abuse this standardization to disguise malicious trap tokens. Unl…

cs.CR2026

Stealthy Backdoor Attacks against LLMs Based on Natural Style Triggers

Jiali Wei, Ming Fan, Guoheng Sun +3

The growing application of large language models (LLMs) in safety-critical domains has raised urgent concerns about their security. Many recent studies have demonstrated the feasib…

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