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Song Liu

4 papers hereh-index 586 citations6 works total

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

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ML2
  • cs.CV1
  • cs.RO1
same name
  • Song Liu — 31 papers, h 20
  • Song Liu — 31 papers, h 11
  • Song Liu — 27 papers, h 26
  • Song Liu — 23 papers, h 14
  • Song Liu — 18 papers, h 26
  • Song Liu — 7 papers, 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

most citedMonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows

2 citations · 3 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model

Team Seedance, Heyi Chen, Siyan Chen +194

Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…

cs.RO2025

FastUMI-100K: Advancing Data-driven Robotic Manipulation with a Large-scale UMI-style Dataset

Kehui Liu, Zhongjie Jia, Yang Li +14

Data-driven robotic manipulation learning depends on large-scale, high-quality expert demonstration datasets. However, existing datasets, which primarily rely on human teleoperated…

stat.ML2023★ 1 cited

Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows

Mingxuan Yi, Song Liu

Variational inference is a technique that approximates a target distribution by optimizing within the parameter space of variational families. On the other hand, Wasserstein gradie…

stat.ML2023★ 2 cited

MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows

Mingxuan Yi, Zhanxing Zhu, Song Liu

The conventional understanding of adversarial training in generative adversarial networks (GANs) is that the discriminator is trained to estimate a divergence, and the generator le…

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