8 accepted papers
Model-based reinforcement learning (RL) offers a compelling approach to offline RL by enabling value learning on imagined on-policy trajectories. However, it often suffers from compounding errors due to repeated model inference. While geometric horizon models (GHM) alleviate this issue through direc…
Training agents that are robust to environmental changes remains a significant challenge in deep reinforcement learning (RL). Unsupervised environment design (UED) has recently emerged to address this issue by generating a set of training environments tailored to the agent's capabilities. While prio…
Existing multi-hop question generation (QG) methods treat answer-irrelevant documents as non-essential and remove them as impurities. However, this approach can create a training-inference discrepancy when impurities cannot be completely removed, which can lead to a decrease in model performance. To…
In the realm of autonomous agents, ensuring safety and reliability in complex and dynamic environments remains a paramount challenge. Safe reinforcement learning addresses these concerns by introducing safety constraints, but still faces challenges in navigating intricate environments such as comple…
We address the problem of developing an accurate but efficient antispoofing (AS) approach in fingerprint biometric recognition on a smart card. To meet low-power constraints for smartcards, we propose a simple convolutional neural network-based architecture and dedicated hardware to handle the probl…
Satisfying safety constraints in reinforcement learning (RL) is an important issue, especially in real-world applications. Many studies have approached safe RL with the Lagrangian method, which introduces dual variables. However, applying a trained policy with the optimal dual variable to a new envi…
Visual Question Answering (VQA) stands to benefit from the boost of increasingly sophisticated Pretrained Language Model (PLM) and Computer Vision-based models. In particular, many language modality studies have been conducted using image captioning or question generation with the knowledge ground o…
Designing a socially-aware navigation method for crowded environments has become a critical issue in robotics. In order to perform navigation in a crowded environment without causing discomfort to nearby pedestrians, it is necessary to design a global planner that is able to consider both human-robo…