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Shuo Chen

14 papers hereh-index 9186 citations16 works total

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

author position
  • first author4
  • middle author9

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV5
  • cs.CL3
  • cs.LG3
  • cs.CR2
  • cs.AI1
same name
  • Shuo Chen — 14 papers, h 20
  • Shuo Chen — 11 papers, h 6
  • Shuo Chen — 8 papers, h 8
  • Shuo Chen — 7 papers, h 4
  • Shuo Chen — 7 papers, h 4
  • Shuo Chen — 6 papers, h 4

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
20222026
most citedCan Multimodal Large Language Models Truly Perform Multimodal In-Context Learning?

5 citations · 5 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model

Yilun Liu, Yunpu Ma, Shuo Chen +4

The Mixture-of-Experts (MoE) paradigm has emerged as a powerful approach for scaling transformers with improved resource utilization. However, efficiently fine-tuning MoE models re…

cs.CL2024

Visual Question Decomposition on Multimodal Large Language Models

Haowei Zhang, Jianzhe Liu, Zhen Han +5

Question decomposition has emerged as an effective strategy for prompting Large Language Models (LLMs) to answer complex questions. However, while existing methods primarily focus…

cs.LG2024

Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?

Shuo Chen, Zhen Han, Bailan He +5

Various jailbreak attacks have been proposed to red-team Large Language Models (LLMs) and revealed the vulnerable safeguards of LLMs. Besides, some methods are not limited to the t…

cs.CV2024

Stop Reasoning! When Multimodal LLM with Chain-of-Thought Reasoning Meets Adversarial Image

Zefeng Wang, Zhen Han, Shuo Chen +6

Multimodal LLMs (MLLMs) with a great ability of text and image understanding have received great attention. To achieve better reasoning with MLLMs, Chain-of-Thought (CoT) reasoning…

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