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Hongbin Liu

20 papers hereh-index 11588 citations24 works total

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

author position
  • first author8
  • middle author12

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CR15
  • cs.CV4
  • cs.LG1
same name
  • Hongbin Liu — 18 papers, h 32
  • Hongbin Liu — 13 papers, h 9
  • Hongbin Liu — 12 papers, h 6
  • Hongbin Liu — 12 papers, h 3
  • Hongbin Liu — 8 papers, h 41
  • Hongbin Liu — 7 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
20202026
most citedPointGuard: Provably Robust 3D Point Cloud Classification

6 citations · 37 across the 19 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection

Zedian Shao, Hongbin Liu, Yuepeng Hu +1

Multi-modal large language models (MLLMs) have emerged as powerful tools for analyzing Internet-scale image data, offering significant benefits but also raising critical safety and…

cs.CV2024

Automatically Generating Visual Hallucination Test Cases for Multimodal Large Language Models

Zhongye Liu, Hongbin Liu, Yuepeng Hu +2

Visual hallucination (VH) occurs when a multimodal large language model (MLLM) generates responses with incorrect visual details for prompts. Existing methods for generating VH tes…

cs.CV2024

Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning

Yuqi Jia, Minghong Fang, Hongbin Liu +2

Poisoning attacks compromise the training phase of federated learning (FL) such that the learned global model misclassifies attacker-chosen inputs called target inputs. Existing de…

cs.CV2024

Visual Hallucinations of Multi-modal Large Language Models

Wen Huang, Hongbin Liu, Minxin Guo +1

Visual hallucination (VH) means that a multi-modal LLM (MLLM) imagines incorrect details about an image in visual question answering. Existing studies find VH instances only in exi…

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