Reinforcement learning (RL) has shown strong potential for autonomous decision-making in complex and dynamic environments. However, its direct application to military systems raises critical safety, reliability, accountability, and verification concerns. Unlike civilian domains, military applications require strict com...
Se-Ik Kim, Hyojun Ahn, Joongheon Kim· International Conference on...· 0 citations
This tutorial addresses the problem of explaining what data re-uploading adds to an amplitude-embedded model and how large the gain is and expresses sequential re-uploading and parallel re-uploading with two copies in one notation and shows that each upload raises the reachable polynomial order by two.
Two-tiered organization provides a compact survey lens for autonomous control (AC): an upper tier supports learning, planning, and high-level (HL) mission reasoning, while a lower tier executes feedback control, safety filtering, and platform-specific constraints. This compact survey reviews hierarchical architectures...
Junseo Min, Hoyeong Lee, Hyojun Ahn et al.· International Conference on...· 0 citations
Results indicate that the proposed framework offers a conservative and computationally deployable offline learning approach for safety-critical underwater autonomous systems, while the present validation is confined to a custom simulation environment, so that operational deployment remains contingent on the hardware-in...
Hyojun Ahn, Hoyeong Lee, Boseon Kang et al.· IEEE Access· 1 citation
Frozen language models (LMs) are increasingly used as fixed feature extractors for downstream reranking, scoring, and preference modeling, raising a practical question: how should a compact module represent interactions among features in a fixed low-dimensional bottleneck? Common linear and low-rank adapters remain lin...
E. Roh, Hyojun Ahn, Hoyeong Lee et al.· 0 citations
Fidelity-based quantum retrieval ranks candidates by the fidelity between query and archive states. Applying a shared input-independent unitary after fixed state encoding leaves that fidelity unchanged, so training the circuit cannot alter the ranking. Quantum parameter-efficient input-dependent retrieval adaptation (Q...
Hyojun Ahn, E. Roh, Soohyun Park et al.· 0 citations
This paper proposes SafeGPT, a hierarchical framework that integrates generative pretrained transformer (GPT)-based large language models (LLM) with safe reinforcement learning (safe-RL). SafeGPT addresses the large-scale random multi-point tour problem (RMPT) for multiple unmanned aerial vehicles (UAVs). The target pl...
Hyojun Ahn, Seungcheol Oh, Gyusun Kim et al.· IEEE Transactions on Network...· 0 citations
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