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Stéphane Lathuilière

13 papers hereh-index 9563 citations20 works total

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

author position
  • first author3
  • middle author8
  • last author2

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

fields
  • cs.CV10
  • cs.AI1
  • cs.RO1
  • cs.SD1
same name
  • Stéphane Lathuilière — 34 papers, h 22
  • Stéphane Lathuilière — 7 papers, h 5
  • Stéphane Lathuilière — 6 papers, h 3
  • Stéphane Lathuilière — 3 papers, h 2
  • Stéphane Lathuilière — 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

activity
20172026
most citedA Comprehensive Analysis of Deep Regression

336 citations · 422 across the 13 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

Reasoning for Social Audio-Visual Question Answering: Where Do We Stand?

Koen P. de Vries, Xavier Alameda-Pineda, Estefanía Talavera +1

Training Multimodal Large Language Models for audio-visual social understanding is a crucial step toward embodied social intelligence. Chain-of-thought (CoT) reasoning has become t…

cs.CV2026

Diffusion Reinforcement Learning via Centered Reward Distillation

Yuanzhi Zhu, Xi Wang, Stéphane Lathuilière +1

Diffusion and flow models achieve State-Of-The-Art (SOTA) generative performance, yet many practically important behaviors such as fine-grained prompt fidelity, compositional corre…

cs.AI2026

Describe-Then-Act: Proactive Agent Steering via Distilled Language-Action World Models

Massimiliano Pappa, Luca Romani, Valentino Sacco +5

Deploying safety-critical agents requires anticipating the consequences of actions before they are executed. While world models offer a paradigm for this proactive foresight, curre…

cs.SD2026

Residual Tokens Enhance Masked Autoencoders for Speech Modeling

Samir Sadok, Stéphane Lathuilière, Xavier Alameda-Pineda

Recent speech modeling relies on explicit attributes such as pitch, content, and speaker identity, but these alone cannot capture the full richness of natural speech. We introduce…

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