Nathan Gavenski

According to our database, Nathan Gavenski authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Zero-Shot Goal Recognition with Large Language Models.

Kin Max Piamolini Gusmão, Nathan Gavenski, Nir Oren, Felipe Meneguzzi

CoRR, May, 2026

Online Goal Recognition using Path Signature and Dynamic Time Warping.

Douglas Antunes Tesch, Nathan Gavenski, Leonardo Amado, Odinaldo Rodrigues, Felipe Meneguzzi

CoRR, May, 2026

When to ASK: Uncertainty-Gated Language Assistance for Reinforcement Learning.

Juarez Monteiro, Nathan Gavenski, Gianlucca L. Zuin, Adriano Veloso

CoRR, April, 2026

Beyond Mimicry: Toward Lifelong Adaptability in Imitation Learning.

Nathan Gavenski, Felipe Meneguzzi, Odinaldo Rodrigues

CoRR, February, 2026

Towards Generalisable Imitation Learning Through Conditioned Transition Estimation and Online Behaviour Alignment.

Nathan Gavenski, Matteo Leonetti, Odinaldo Rodrigues

CoRR, January, 2026

2025

Fairness in Deep Learning: A Survey on Vision and Language Research.

Otávio Parraga, Martin D. Móre, Christian Mattjie de Oliveira, Nathan S. Gavenski, Lucas S. Kupssinskü, Adilson Medronha, Luis Vinícius de Moura, Gabriel S. Simões, Rodrigo C. Barros

ACM Comput. Surv., June, 2025

Quantifying Generalisation in Imitation Learning.

Nathan Gavenski, Odinaldo Rodrigues

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Imitation Learning: A Survey of Learning Methods, Environments and Metrics.

Nathan Gavenski, Odinaldo Rodrigues, Michael Luck

CoRR, 2024

Explorative Imitation Learning: A Path Signature Approach for Continuous Environments.

Nathan Gavenski, Juarez Monteiro, Felipe Meneguzzi, Michael Luck, Odinaldo Rodrigues

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking.

Nathan Gavenski, Michael Luck, Odinaldo Rodrigues

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Self-Supervised Adversarial Imitation Learning.

Juarez Monteiro, Nathan Gavenski, Felipe Meneguzzi, Rodrigo C. Barros

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey.

Otávio Parraga, Martin D. Móre, Christian Mattjie de Oliveira, Nathan S. Gavenski, Lucas S. Kupssinskü, Adilson Medronha, Luis Vinícius de Moura, Gabriel S. Simões, Rodrigo C. Barros

CoRR, 2022

Efficient Counterfactual Debiasing for Visual Question Answering.

Camila Kolling, Martin D. Móre, Nathan Gavenski, Eduardo H. P. Pooch, Otávio Parraga, Rodrigo C. Barros

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

How Resilient Are Imitation Learning Methods to Sub-optimal Experts?

Nathan Gavenski, Juarez Monteiro, Adilson Medronha, Rodrigo C. Barros

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2020

Object-Based Goal Recognition Using Real-World Data.

Roger Granada, Juarez Monteiro, Nathan Gavenski, Felipe Meneguzzi

Proceedings of the Advances in Soft Computing, 2020

Attention-based 3D Object Reconstruction from a Single Image.

Andrey de Aguiar Salvi, Nathan Gavenski, Eduardo H. P. Pooch, Felipe Tasoniero, Rodrigo C. Barros

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Augmented Behavioral Cloning from Observation.

Juarez Monteiro, Nathan Gavenski, Roger Granada, Felipe Meneguzzi, Rodrigo C. Barros

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Imitating Unknown Policies via Exploration.

Nathan Gavenski, Juarez Monteiro, Roger Granada, Felipe Meneguzzi, Rodrigo C. Barros

Proceedings of the 31st British Machine Vision Conference 2020, 2020