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Song Han

19 papers hereh-index 132.3k citations22 works total

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

author position
  • middle author15
  • last author3

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.LG2
  • cs.AI1
  • cs.RO1
same name
  • Song Han — 52 papers, h 55
  • Song Han — 37 papers, h 15
  • Song Han — 17 papers, h 16
  • Song Han — 12 papers, h 10
  • Song Han — 12 papers, h 8
  • Song Han — 7 papers, h 19

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
20232026
most citedVILA: On Pre-training for Visual Language Models

6 citations · 13 across the 18 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024★ 1 cited

VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Yecheng Wu, Zhuoyang Zhang, Junyu Chen +9

VILA-U is a Unified foundation model that integrates Video, Image, Language understanding and generation. Traditional visual language models (VLMs) use separate modules for underst…

cs.CV2024★ 1 cited

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Yukang Chen, Fuzhao Xue, Dacheng Li +15

Long-context capability is critical for multi-modal foundation models, especially for long video understanding. We introduce LongVILA, a full-stack solution for long-context visual…

cs.CV2024

VILA2: VILA Augmented VILA

Yunhao Fang, Ligeng Zhu, Yao Lu +7

While visual language model architectures and training infrastructures advance rapidly, data curation remains under-explored where quantity and quality become a bottleneck. Existin…

cs.CV2024★ 1 cited

X-VILA: Cross-Modality Alignment for Large Language Model

Hanrong Ye, De-An Huang, Yao Lu +8

We introduce X-VILA, an omni-modality model designed to extend the capabilities of large language models (LLMs) by incorporating image, video, and audio modalities. By aligning mod…

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