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researcher

Laurence T. Yang

4 papers hereh-index 7164 citations11 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
  • cs.CV3
  • cs.LG1
same name
  • Laurence T. Yang — 7 papers, h 3
  • Laurence T. Yang — 5 papers, h 4
  • Laurence T. Yang — 1 paper, h 0
  • Laurence T. Yang — 1 paper, h 8
  • Laurence T. Yang — 1 paper, h 1
  • Laurence T. Yang — 1 paper

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 citedGeneral Point Model with Autoencoding and Autoregressive

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

collaborators

4 papers

cs.CV2024

LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning

Zhe Li, Weihao Yuan, Yisheng He +7

Language plays a vital role in the realm of human motion. Existing methods have largely depended on CLIP text embeddings for motion generation, yet they fall short in effectively a…

cs.CV2024★ 1 cited

MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning

Zhe Li, Laurence T. Yang, Bocheng Ren +4

The scarcity of annotated data has sparked significant interest in unsupervised pre-training methods that leverage medical reports as auxiliary signals for medical visual represent…

cs.CV2024

Mitigating Prior Shape Bias in Point Clouds via Differentiable Center Learning

Zhe Li, Xiying Wang, Jinglin Zhao +3

Masked autoencoding and generative pretraining have achieved remarkable success in computer vision and natural language processing, and more recently, they have been extended to th…

cs.LG2023★ 1 cited

General Point Model with Autoencoding and Autoregressive

Zhe Li, Zhangyang Gao, Cheng Tan +2

The pre-training architectures of large language models encompass various types, including autoencoding models, autoregressive models, and encoder-decoder models. We posit that any…

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