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Zhenguang Liu

4 papers hereh-index 223 citations5 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.AI1
  • cs.CR1
  • cs.CV1
  • cs.SE1
same name
  • Zhenguang Liu — 19 papers, h 20
  • Zhenguang Liu — 15 papers, h 22
  • Zhenguang Liu — 10 papers, h 9
  • Zhenguang Liu — 7 papers, h 4
  • Zhenguang Liu — 2 papers, h 2
  • Zhenguang Liu — 1 paper, 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 citedLet All be Whitened: Multi-teacher Distillation for Efficient Visual Retrieval

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.SE2026

From Approval to Execution: Reconstruction-Aware Repair Analysis for LLM-Agent Software

Junchi Zhu, Zhenguang Liu, Shaojing Fan +2

Approval mechanisms have become a primary safeguard for consequential actions in LLM-agent software. Yet the action shown for approval is often not the object ultimately consumed:…

cs.AI2026

Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls

Guoyao Yu, Xiaoqing Sun, Ziqi Huang +13

Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool and orchestrating the order…

cs.CR2026

Poster: Rethinking Security in LLM Code Generation through Real-World Risk Scenarios

Lixun Ma, Ruolong Ma, Bei Wang +4

Large Language Models (LLMs) are widely used for code generation, yet their security behavior in realistic development workflows remains underexplored. Existing benchmarks often re…

cs.CV2023★ 1 cited

Let All be Whitened: Multi-teacher Distillation for Efficient Visual Retrieval

Zhe Ma, Jianfeng Dong, Shouling Ji +7

Visual retrieval aims to search for the most relevant visual items, e.g., images and videos, from a candidate gallery with a given query item. Accuracy and efficiency are two compe…

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