From the 1 of 7 linked papers with an AI index.
7 papers
Measuring Fairness in Large Audio Language Models via Semantic-Aware Bias Estimation
Zhe Liu
Large Audio Language Models (LALMs) have seen increasing use for audio understanding tasks such as speech recognition and audio question answering, raising concerns about fairness…
Active Offline-to-Online Reinforcement Learning
Alper Kamil Bozkurt, Shangtong Zhang, Yuichi Motai
The paper proposes an active selection method for fine‑tuning offline‑trained policies under a limited online interaction budget, using upper‑confidence bounds derived from linear…
Architecture-Adaptive Uncertainty Fusion for Deepfake Detection
Ritesh Sharma, Mohammad Ghasemigol, Yuichi Motai
Deepfake detection systems achieve near-perfect accuracy on benchmarks, yet forensic deployment demands reliable prediction uncertainty. Existing uncertainty quantification (UQ) me…
Uncertainty-Aware Adaptive Sensor Fusion for Autonomous Navigation
Simegnew Yihunie Alaba, Yuichi Motai
This work introduces a hybrid deep learning approach integrated with an Unscented Kalman Filter (UKF) to enhance pose estimation accuracy in Visual-Inertial Odometry (VIO) for auto…
Multi-Column RBF Neural Network Using Adaptive and Non-Adaptive Particle Swarm Optimization
Ammar Hoori, Yuichi Motai
The radial basis function neural network (RBFN) trained with a gradient descending algorithm provides an effective fully connected structure in both shallow and deep networks. The…
Safe In-Context Reinforcement Learning
Amir Moeini, Minjae Kwon, Alper Kamil Bozkurt +4
In-context reinforcement learning (ICRL) is an emerging RL paradigm where an agent, after pretraining, can adapt to out-of-distribution test tasks without any parameter updates, in…