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Yunhui Guo

11 papers hereh-index 534 citations14 works total

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

author position
  • middle author6
  • last author5

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.SD3
  • cs.LG2
same name
  • Yunhui Guo — 13 papers, h 16
  • Yunhui Guo — 10 papers, h 3
  • Yunhui Guo — 5 papers, h 2
  • Yunhui Guo — 4 papers, h 3
  • Yunhui Guo — 2 papers, h 3
  • Yunhui Guo — 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 citedModality-Inconsistent Continual Learning of Multimodal Large Language Models

1 citations · 1 across the 9 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

CURE-OOD: Benchmarking Out-of-Distribution Detection for Survival Prediction

Wenjie Zhao, Jia Li, Mingrui Liu +2

``How long can I live and remain free of cancer?'' is often the first question a patient asks after receiving a cancer diagnosis and treatment. Accurate survival prediction helps a…

cs.SD2026

OmniSonic: Towards Universal and Holistic Audio Generation from Video and Text

Weiguo Pian, Saksham Singh Kushwaha, Zhimin Chen +4

In this paper, we propose Universal Holistic Audio Generation (UniHAGen), a task for synthesizing comprehensive auditory scenes that include both on-screen and off-screen sounds ac…

cs.CV2026

A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding

Yue Zhang, Liqiang Jing, Jia Li +4

Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos remains limited. Existing approa…

cs.LG2026

Audio-Visual Continual Test-Time Adaptation without Forgetting

Sarthak Kumar Maharana, Akshay Mehra, Bhavya Ramakrishna +2

Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary domains, where either or both modali…

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