339 citations · 354 across the 8 of their papers we have counts for
8 papers
Learning To Explore With Predictive World Model Via Self-Supervised Learning
Alana Santana, Paula P. Costa, Esther L. Colombini
Autonomous artificial agents must be able to learn behaviors in complex environments without humans to design tasks and rewards. Designing these functions for each environment is n…
InstructRobot: A Model-Free Framework for Mapping Natural Language Instructions into Robot Motion
Iury Cleveston, Alana C. Santana, Paula D. P. Costa +3
The ability to communicate with robots using natural language is a significant step forward in human-robot interaction. However, accurately translating verbal commands into physica…
Should I disclose my dataset? Caveats between reproducibility and individual data rights
Raysa M. Benatti, Camila M. L. Villarroel, Sandra Avila +2
Natural language processing techniques have helped domain experts solve legal problems. Digital availability of court documents increases possibilities for researchers, who can acc…
A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems
Rafael Figueiredo Prudencio, Marcos R. O. A. Maximo, Esther Luna Colombini
With the widespread adoption of deep learning, reinforcement learning (RL) has experienced a dramatic increase in popularity, scaling to previously intractable problems, such as pl…
Neural Attention Models in Deep Learning: Survey and Taxonomy
Alana Santana, Esther Colombini
Attention is a state of arousal capable of dealing with limited processing bottlenecks in human beings by focusing selectively on one piece of information while ignoring other perc…
CIDEr-R: Robust Consensus-based Image Description Evaluation
Gabriel Oliveira dos Santos, Esther Luna Colombini, Sandra Avila
This paper shows that CIDEr-D, a traditional evaluation metric for image description, does not work properly on datasets where the number of words in the sentence is significantly…
RAM-VO: Less is more in Visual Odometry
Iury Cleveston, Esther L. Colombini
Building vehicles capable of operating without human supervision requires the determination of the agent's pose. Visual Odometry (VO) algorithms estimate the egomotion using only v…
A comparative evaluation of learned feature descriptors on hybrid monocular visual SLAM methods
Hudson M. S. Bruno, Esther L. Colombini
Classical Visual Simultaneous Localization and Mapping (VSLAM) algorithms can be easily induced to fail when either the robot's motion or the environment is too challenging. The us…