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Jingjing Liu

5 papers hereh-index 61.5k citations6 works total

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

author position
  • middle author4
  • last author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Jingjing Liu — 62 papers, h 48
  • Jingjing Liu — 17 papers, h 12
  • Jingjing Liu — 12 papers, h 10
  • Jingjing Liu — 11 papers, h 11
  • Jingjing Liu — 7 papers, h 5
  • Jingjing Liu — 5 papers, h 3

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 citedEmu: Generative Pretraining in Multimodality

29 citations · 45 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024★ 4 cited

Emu3: Next-Token Prediction is All You Need

Xinlong Wang, Xiaosong Zhang, Zhengxiong Luo +22

While next-token prediction is considered a promising path towards artificial general intelligence, it has struggled to excel in multimodal tasks, which are still dominated by diff…

cs.CV2023★ 7 cited

Generative Multimodal Models are In-Context Learners

Quan Sun, Yufeng Cui, Xiaosong Zhang +8

The human ability to easily solve multimodal tasks in context (i.e., with only a few demonstrations or simple instructions), is what current multimodal systems have largely struggl…

cs.CV2023★ 2 cited

CapsFusion: Rethinking Image-Text Data at Scale

Qiying Yu, Quan Sun, Xiaosong Zhang +5

Large multimodal models demonstrate remarkable generalist ability to perform diverse multimodal tasks in a zero-shot manner. Large-scale web-based image-text pairs contribute funda…

cs.CV2023★ 29 cited

Emu: Generative Pretraining in Multimodality

Quan Sun, Qiying Yu, Yufeng Cui +7

We present Emu, a Transformer-based multimodal foundation model, which can seamlessly generate images and texts in multimodal context. This omnivore model can take in any single-mo…

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