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Ying-Cong Chen

4 papers hereh-index 597 citations5 works total

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

author position
  • middle author1
  • last author3

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

fields
  • cs.CV3
  • cs.LG1
same name
  • Ying-Cong Chen — 16 papers, h 6
  • Ying-Cong Chen — 13 papers
  • Ying-Cong Chen — 9 papers, h 4
  • Ying-Cong Chen — 9 papers, h 3
  • Ying-Cong Chen — 8 papers, h 3
  • Ying-Cong Chen — 8 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

most citedMTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2025

V-ReasonBench: Toward Unified Reasoning Benchmark Suite for Video Generation Models

Yang Luo, Xuanlei Zhao, Baijiong Lin +7

Recent progress in generative video models, such as Veo-3, has shown surprising zero-shot reasoning abilities, creating a growing need for systematic and reliable evaluation. We in…

cs.LG2025

PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model

Baijiong Lin, Weisen Jiang, Yuancheng Xu +2

Multi-objective test-time alignment aims to adapt large language models (LLMs) to diverse multi-dimensional user preferences during inference while keeping LLMs frozen. Recently, G…

cs.CV2024

MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders

Baijiong Lin, Weisen Jiang, Pengguang Chen +2

Multi-task dense scene understanding, which trains a model for multiple dense prediction tasks, has a wide range of application scenarios. Capturing long-range dependency and enhan…

cs.CV2024★ 1 cited

MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders

Baijiong Lin, Weisen Jiang, Pengguang Chen +3

Multi-task dense scene understanding, which learns a model for multiple dense prediction tasks, has a wide range of application scenarios. Modeling long-range dependency and enhanc…

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