7 citations · 7 across the 4 of their papers we have counts for
5 papers
Improving Cross-embodiment Transfer in Latent Action Models with Action-Similarity Supervision
Maxime Alvarez, Renzo Caballero, Tatsuya Matsushima +2
As generalist robot policies gain vision and language from web-scale pretraining, demonstrations remain costly to collect and tied to the robot that recorded them. Latent action mo…
When Absolute State Fails: Evaluating Proprioceptive Encodings for Robust Manipulation
Maxime Alvarez, Ryo Watanabe, Paul Crook +4
As end-to-end robotic policies are progressively deployed in the real world to solve real tasks, they face a gap between the training and inference conditions. Scaling the amount a…
Leave No Observation Behind: Real-time Correction for VLA Action Chunks
Kohei Sendai, Maxime Alvarez, Tatsuya Matsushima +2
To improve efficiency and temporal coherence, Vision-Language-Action (VLA) models often predict action chunks; however, this action chunking harms reactivity under inference delay…
FTACT: Force Torque aware Action Chunking Transformer for Pick-and-Reorient Bottle Task
Ryo Watanabe, Maxime Alvarez, Pablo Ferreiro +2
Manipulator robots are increasingly being deployed in retail environments, yet contact rich edge cases still trigger costly human teleoperation. A prominent example is upright lyin…
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms
Maxime Alvarez, Jean-Charles Verdier, D'Jeff K. Nkashama +3
Anomaly detection has many applications ranging from bank-fraud detection and cyber-threat detection to equipment maintenance and health monitoring. However, choosing a suitable al…