9+ hour, 55+ min ago   (496+ words) Offline reinforcement learning (offline RL) and large-language-model (LLM) alignment are typically studied as independent domains and each has developed its own pairwise comparison technique. Prior studies have validated pairwise classification exclusively within offline RL, leaving open the question of whether it…...

1+ day, 1+ hour ago   (361+ words) This research investigates the security of large language models (LLMs) with the aim of identifying key security and safety threats, control measures, and governance considerations that are relevant to their trustworthy adoption in the Extended Reality (XR) domain. To achieve…...

1+ day, 4+ hour ago   (678+ words) Mapless deep reinforcement learning (DRL) navigation in dynamic indoor environments is difficult under single-frame 2D LiDAR, which reports where an obstacle is but not whether it is approaching. We introduce the Positional-Velocity Spatio-Temporal Attention Module (PV-STAM), a compact perception block (19,968 trainable…...

2+ day, 4+ hour ago   (496+ words) Aspect-based sentiment analysis (ABSA) aims to identify the sentiment polarity expressed toward a specific aspect in a sentence. Existing sequential and Transformer-based methods can effectively capture contextual semantics, but they often lack explicit modeling of aspect–opinion relations. Graph-based approaches…...

3+ day, 22+ hour ago   (533+ words) This study proposes EQAS (Empowered Question-Answering System), a hybrid framework designed to support context-aware question-answering and intelligent feedback generation in domain-specific knowledge environments. EQAS integrates fine-tuned transformer-based models, instruction-guided large language models, domain-specific knowledge graphs, and LangChain-based vector retrieval to…...

3+ day, 22+ hour ago   (571+ words) Deep neural networks (DNNs) are widely deployed in safety-critical applications such as medical diagnosis and autonomous driving. Adversarial training (AT) is among the most effective defenses, casting robust optimization as a min–max problem over a defender-specified ℓp-ball of fixed…...

3+ day, 23+ hour ago   (688+ words) Digital twins (DTs) based on agent-based artificial intelligence (Agentic AI) provide a transformative framework for streamlining nondestructive testing (NDT) of 3D-printed rehabilitation equipment. This study applies a conceptual research methodology based on the integration and analysis of recent advances in…...

4+ day, 1+ hour ago   (411+ words) Time-series representation learning decomposes signals into interpretable factors such as trend and seasonality, and disentangled representation learning assigns these factors to distinct latent dimensions, enhancing interpretability and forecasting accuracy. However, existing methods achieve only statistical disentanglement: an intervention on one…...

4+ day, 6+ hour ago   (532+ words) Camera-only BEV 3D object detectors are trained under highly imbalanced category distributions, and their matched object queries can exhibit directional semantic errors toward frequent classes. We investigate this behavior as a diagnostic problem: given fixed geometric predictions and fixed query–ground-truth…...

4+ day, 23+ hour ago   (584+ words) Predicting queue waiting time for batch job schedulers in high-performance computing (HPC) systems is a critical research topic aimed at maximizing resource utilization efficiency and enhancing user experience. However, existing prediction approaches heavily rely on static job characteristics provided by…...