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Yann LeCun

8 papers hereh-index 8143 citations18 works total

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

author position
  • middle author7
  • last author1

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.RO4
same name
  • Yann LeCun — 68 papers, h 139
  • Yann LeCun — 40 papers, h 22
  • Yann LeCun — 39 papers, h 12
  • Yann LeCun — 18 papers
  • Yann LeCun — 1 paper, h 1
  • Yann LeCun — 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 citedForgotten Polygons: Multimodal Large Language Models are Shape-Blind

2 citations · 4 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025★ 1 cited

VL-JEPA: Joint Embedding Predictive Architecture for Vision-language

Delong Chen, Mustafa Shukor, Theo Moutakanni +7

We introduce VL-JEPA, a vision-language model built on a Joint Embedding Predictive Architecture (JEPA). Instead of autoregressively generating tokens as in classical VLMs, VL-JEPA…

cs.CV2025

Whole-Body Conditioned Egocentric Video Prediction

Yutong Bai, Danny Tran, Amir Bar +3

We train models to Predict Ego-centric Video from human Actions (PEVA), given the past video and an action represented by the relative 3D body pose. By conditioning on kinematic po…

cs.CV2025★ 2 cited

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind

William Rudman, Michal Golovanevsky, Amir Bar +4

Despite strong performance on vision-language tasks, Multimodal Large Language Models (MLLMs) struggle with mathematical problem-solving, with both open-source and state-of-the-art…

cs.CV2024

Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning

Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon +7

AI Foundation models are gaining traction in various applications, including medical fields like radiology. However, medical foundation models are often tested on limited tasks, le…

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