2 citations · 3 across the 7 of their papers we have counts for
7 papers
Mining the Long Tail: A Comparative Study of Data-Centric Criticality Metrics for Robust Offline Reinforcement Learning in Autonomous Motion Planning
Antonio Guillen-Perez
Offline Reinforcement Learning (RL) presents a promising paradigm for training autonomous vehicle (AV) planning policies from large-scale, real-world driving logs. However, the ext…
Efficient Virtuoso: A Latent Diffusion Transformer Model for Goal-Conditioned Trajectory Planning
Antonio Guillen-Perez
The ability to generate a diverse and plausible distribution of future trajectories is a critical capability for autonomous vehicle planning systems. While recent generative models…
From Imitation to Optimization: A Comparative Study of Offline Learning for Autonomous Driving
Antonio Guillen-Perez
Learning robust driving policies from large-scale, real-world datasets is a central challenge in autonomous driving, as online data collection is often unsafe and impractical. Whil…
N-Critics: Self-Refinement of Large Language Models with Ensemble of Critics
Sajad Mousavi, Ricardo Luna Gutiérrez, Desik Rengarajan +5
We propose a self-correction mechanism for Large Language Models (LLMs) to mitigate issues such as toxicity and fact hallucination. This method involves refining model outputs thro…
Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness
Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi +6
We present a novel framework for generating adversarial benchmarks to evaluate the robustness of image classification models. Our framework allows users to customize the types of d…
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels
Alexander Shmakov, Avisek Naug, Vineet Gundecha +5
Bayesian Optimization (BO), guided by Gaussian process (GP) surrogates, has proven to be an invaluable technique for efficient, high-dimensional, black-box optimization, a critical…
PyDCM: Custom Data Center Models with Reinforcement Learning for Sustainability
Avisek Naug, Antonio Guillen, Ricardo Luna Gutiérrez +8
The increasing global emphasis on sustainability and reducing carbon emissions is pushing governments and corporations to rethink their approach to data center design and operation…