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researcher

Tianhang Zheng

24 papers hereh-index 445 citations25 works total

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

author position
  • middle author17
  • last author2

Across the 19 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CR12
  • cs.AI6
  • cs.CL2
  • cs.LG2
  • cs.DC1
  • cs.NI1
same name
  • Tianhang Zheng — 9 papers, h 5
  • Tianhang Zheng — 7 papers, h 7
  • Tianhang Zheng — 4 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

activity
20242026
most citedHybridFlow: Resource-Adaptive Subtask Routing for Efficient Edge-Cloud LLM Inference

1 citations · 2 across the 20 of their papers we have counts for

collaborators
Showing 2025 · cs.CRShow all

4 papers · 2 filters

cs.CR2025

NonTextual Target Attack

Xinzhe Huang, Wenjing Hu, Tianhang Zheng +6

Existing gradient-based jailbreak attacks on Large Language Models (LLMs) typically optimize adversarial suffixes to align the LLM output with predefined target responses. However,…

cs.CR2025

Dynamic Jailbreaking Attack

Kedong Xiu, Yunhan Yang, Churui Zeng +6

Existing gradient-based jailbreak attacks typically optimize a fixed-length adversarial suffix toward a predefined target response with a static optimization strategy. However, thi…

cs.CR2025★ 1 cited

MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies

Weiwei Qi, Shuo Shao, Wei Gu +4

Large Language Models (LLMs) have exhibited remarkable capabilities but remain vulnerable to jailbreaking attacks, which can elicit harmful content from the models by manipulating…

cs.CR2025

DualBreach: Efficient Dual-Jailbreaking via Target-Driven Initialization and Multi-Target Optimization

Xinzhe Huang, Kedong Xiu, Tianhang Zheng +5

Recent research has focused on exploring the vulnerabilities of Large Language Models (LLMs), aiming to elicit harmful and/or sensitive content from LLMs. However, due to the insuf…

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