Support Vector Data Description for Radar Target Detection
arXiv:2602.18486v1 Announce Type: new
Abstract: Classical radar detection techniques rely on adaptive detectors that estimate the noise covariance matrix from target-free secondary data. While effective in Gaussian environments, these methods degrade in the presence of clutter, which is better mode...
Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge
arXiv:2602.17826v1 Announce Type: new
Abstract: Language models exhibit fundamental limitations -- hallucination, brittleness, and lack of formal grounding -- that are particularly problematic in high-stakes specialist fields requiring verifiable reasoning. I investigate whether formal domain ontol...
When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation
arXiv:2602.16763v1 Announce Type: new
Abstract: Artificial Intelligence (AI) benchmarks play a central role in measuring progress in model development and guiding deployment decisions. However, many benchmarks quickly become saturated, meaning that they can no longer differentiate between the best-...
AIdentifyAGE Ontology for Decision Support in Forensic Dental Age Assessment
arXiv:2602.16714v1 Announce Type: new
Abstract: Age assessment is crucial in forensic and judicial decision-making, particularly in cases involving undocumented individuals and unaccompanied minors, where legal thresholds determine access to protection, healthcare, and judicial procedures. Dental a...
Real-time Secondary Crash Likelihood Prediction Excluding Post Primary Crash Features
arXiv:2602.16739v1 Announce Type: new
Abstract: Secondary crash likelihood prediction is a critical component of an active traffic management system to mitigate congestion and adverse impacts caused by secondary crashes. However, existing approaches mainly rely on post-crash features (e.g., crash t...
MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior
arXiv:2602.16730v1 Announce Type: new
Abstract: Accurate speed prediction is crucial for proactive traffic management to enhance traffic efficiency and safety. Existing studies have primarily relied on aggregated, macroscopic traffic flow data to predict future traffic trends, whereas road traffic ...
Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
arXiv:2602.16012v1 Announce Type: new
Abstract: Neural solvers have achieved impressive progress in addressing simple routing problems, particularly excelling in computational efficiency. However, their advantages under complex constraints remain nascent, for which current constraint-handling schem...
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
arXiv:2602.15159v1 Announce Type: new
Abstract: Learning from electronic health records (EHRs) time series is challenging due to irregular sam- pling, heterogeneous missingness, and the resulting sparsity of observations. Prior self-supervised meth- ods either impute before learning, represent miss...
LLM Embeddings vs TF-IDF vs Bag-of-Words: Which Works Better in Scikit-learn?
Machine learning models built with frameworks like scikit-learn can accommodate unstructured data like text, as long as this raw text is converted into a numerical representation that is understandable by algorithms, models, and machines in a broader sense.
Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications
arXiv:2602.12338v1 Announce Type: new
Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications and computations, enabling efficient digital semantic- and goal-oriented communications in future wirele...
Explaining AI Without Code: A User Study on Explainable AI
arXiv:2602.11159v1 Announce Type: new
Abstract: The increasing use of Machine Learning (ML) in sensitive domains such as healthcare, finance, and public policy has raised concerns about the transparency of automated decisions. Explainable AI (XAI) addresses this by clarifying how models generate pr...
On Decision-Valued Maps and Representational Dependence
arXiv:2602.11295v1 Announce Type: new
Abstract: A computational engine applied to different representations of the same data can produce different discrete outcomes, with some representations preserving the result and others changing it entirely. A decision-valued map records which representations ...
KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
arXiv:2602.11184v1 Announce Type: new
Abstract: Mixture of Experts (MoE) models have achieved great success by significantly improving performance while maintaining computational efficiency through sparse expert activation. However, their enormous parameter sizes and memory demands pose major chall...
arXiv:2602.10195v1 Announce Type: new
Abstract: A novel sequence architecture design is introduced, Versor, which uses Conformal Geometric Algebra (CGA) in place of the traditional fundamental non-linear operations to achieve structural generalization and significant performance improvements on a v...
Adaptive Optimization via Momentum on Variance-Normalized Gradients
arXiv:2602.10204v1 Announce Type: new
Abstract: We introduce MVN-Grad (Momentum on Variance-Normalized Gradients), an Adam-style optimizer that improves stability and performance by combining two complementary ideas: variance-based normalization and momentum applied after normalization. MVN-Grad sc...
Lagged backward-compatible physics-informed neural networks for unsaturated soil consolidation analysis
arXiv:2602.07031v1 Announce Type: new
Abstract: This study develops a Lagged Backward-Compatible Physics-Informed Neural Network (LBC-PINN) for simulating and inverting one-dimensional unsaturated soil consolidation under long-term loading. To address the challenges of coupled air and water pressur...
MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation
arXiv:2602.05048v1 Announce Type: new
Abstract: Joint planning through language-based interactions is a key area of human-AI teaming. Planning problems in the open world often involve various aspects of incomplete information and unknowns, e.g., objects involved, human goals/intents -- thus leading...
Active Epistemic Control for Query-Efficient Verified Planning
arXiv:2602.03974v1 Announce Type: new
Abstract: Planning in interactive environments is challenging under partial observability: task-critical preconditions (e.g., object locations or container states) may be unknown at decision time, yet grounding them through interaction is costly. Learned world ...
Learning ORDER-Aware Multimodal Representations for Composite Materials Design
arXiv:2602.02513v1 Announce Type: new
Abstract: Artificial intelligence (AI) has shown remarkable success in materials discovery and property prediction, particularly for crystalline and polymer systems where material properties and structures are dominated by discrete graph representations. Such g...
Sparse Adapter Fusion for Continual Learning in NLP
arXiv:2602.02502v1 Announce Type: new
Abstract: Continual learning in natural language processing plays a crucial role in adapting to evolving data and preventing catastrophic forgetting. Despite significant progress, existing methods still face challenges, such as inefficient parameter reuse acros...