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researcher

L. Le

16 papers hereh-index 133.6k citations21 works total

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

author position
  • first author1
  • middle author12

Across the 13 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV10
  • eess.IV2
  • cs.AI1
  • cs.CL1
  • cs.LG1
  • q-bio.NC1
same name
  • L. Le — 35 papers, h 51
  • L. Le — 8 papers, h 6
  • L. Le — 8 papers, h 3
  • L. Le — 2 papers, h 5
  • L. Le — 1 paper, h 2
  • L. Le — 1 paper, h 1

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
20222026
most citedMultimodal Whole Slide Foundation Model for Pathology

26 citations · 105 across the 13 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025★ 8 cited

A Foundation Model for Spatial Proteomics

Muhammad Shaban, Yuzhou Chang, Huaying Qiu +57

Foundation models have begun to transform image analysis by acting as pretrained generalist backbones that can be adapted to many tasks even when post-training data are limited, ye…

cs.CV2025★ 1 cited

Evidence-based diagnostic reasoning with multi-agent copilot for human pathology

Luca L. Weishaupt, Chengkuan Chen, Drew F. K. Williamson +8

Pathology is experiencing rapid digital transformation driven by whole-slide imaging and artificial intelligence (AI). While deep learning-based computational pathology has achieve…

cs.CV2025★ 6 cited

AI-driven 3D Spatial Transcriptomics

Cristina Almagro-Pérez, Andrew H. Song, Luca Weishaupt +13

A comprehensive three-dimensional (3D) map of tissue architecture and gene expression is crucial for illuminating the complexity and heterogeneity of tissues across diverse biomedi…

cs.CV2025★ 12 cited

Molecular-driven Foundation Model for Oncologic Pathology

Anurag Vaidya, Andrew Zhang, Guillaume Jaume +15

Foundation models are reshaping computational pathology by enabling transfer learning, where models pre-trained on vast datasets can be adapted for downstream diagnostic, prognosti…

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