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The TSVD (Truncated Singular Value Decomposition) framework which efficiently maintains orthonormality through QR decomposition and caching is presented, and a spectral energy heuristic is introduced to select the rank of the resulting low-rank weight matrices.
High-capacity neural network models have achieved state-of-the-art performance across diverse classification tasks, yet they frequently operate as black-box models, lacking the transparency necessary for critical decision-making. Such opacity creates a persistent trade-off between performance and explainability. This p...
A legal planning stack that employs Defeasible Deontic Logic (DDL) to constrain a motion planner and leverages learned world models to plan and to provide legal context, enabling ex ante governance that intervenes before an illegal action is executed.
Evolution Strategies (ES), a population-based, gradient-free post-training method that optimizes directly in weight space through random perturbations, achieves consistently higher pass@k than RL and produces a broader output distribution with greater solution coverage.
A semantic-uncertainty-guided orchestration approach, HASSUM is introduced as a general framework for uncertainty-aware coordination in multi-agent systems and suggests that semantic uncertainty is a practical and general-purpose signal for improving robustness and trustworthiness in agentic AI systems.
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