A Survey of Freshness-Aware Wireless Networking with Reinforcement Learning
arXiv:2512.21412v1 Announce Type: new
Abstract: The age of information (AoI) has become a central measure of data freshness in modern wireless systems, yet existing surveys either focus on classical AoI formulations or provide broad discussions of reinforcement learning (RL) in wireless networks wi...
A Study of Solving Life-and-Death Problems in Go Using Relevance-Zone Based Solvers
arXiv:2512.21365v1 Announce Type: new
Abstract: This paper analyzes the behavior of solving Life-and-Death (L&D) problems in the game of Go using current state-of-the-art computer Go solvers with two techniques: the Relevance-Zone Based Search (RZS) and the relevance-zone pattern table. We examined...
Proceedings of the 20th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2025)
arXiv:2512.20628v1 Announce Type: new
Abstract: This volume presents the proceedings of the 20th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2025), held in Nagaoka, Japan, on December 3-5, 2025. The conference, organized in cooperation with the IEICE Pro...
arXiv:2512.16928v1 Announce Type: new
Abstract: The Muon optimizer enjoys strong empirical performance and theoretical grounding. However, the super-linear cost of its orthonormalization step introduces increasing overhead with scale. To alleviate this cost, several works have attempted to reduce t...
SHARe-KAN: Holographic Vector Quantization for Memory-Bound Inference
arXiv:2512.15742v1 Announce Type: new
Abstract: Kolmogorov-Arnold Networks (KANs) face a fundamental memory wall: their learned basis functions create parameter counts that impose extreme bandwidth demands, hindering deployment in memory-constrained environments. We show that Vision KANs exhibit a ...
Improving Underwater Acoustic Classification Through Learnable Gabor Filter Convolution and Attention Mechanisms
arXiv:2512.14714v1 Announce Type: new
Abstract: Remotely detecting and classifying underwater acoustic targets is critical for environmental monitoring and defence. However, the complex nature of ship-radiated and environmental underwater noise poses significant challenges to accurate signal proces...
SepsisSuite: Beyond Risk Stratification -- A Comparative Analysis of Deep Fusion vs. Expert Stacking for Prescriptive Sepsis AI
arXiv:2512.14712v1 Announce Type: new
Abstract: Sepsis accounts for nearly 20% of global ICU admissions, yet conventional prediction models often fail to effectively integrate heterogeneous data streams, remaining either siloed by modality or reliant on brittle early fusion. In this work, we presen...
Robust Gradient Descent via Heavy-Ball Momentum with Predictive Extrapolation
arXiv:2512.10033v1 Announce Type: new
Abstract: Accelerated gradient methods like Nesterov's Accelerated Gradient (NAG) achieve faster convergence on well-conditioned problems but often diverge on ill-conditioned or non-convex landscapes due to aggressive momentum accumulation. We propose Heavy-Bal...
BAMBO: Construct Ability and Efficiency LLM Pareto Set via Bayesian Adaptive Multi-objective Block-wise Optimization
arXiv:2512.09972v1 Announce Type: new
Abstract: Constructing a Pareto set is pivotal for navigating the capability-efficiency trade-offs in Large Language Models (LLMs); however, existing merging techniques remain inadequate for this task. Coarse-grained, model-level methods yield only a sparse set...
HGC-Herd: Efficient Heterogeneous Graph Condensation via Representative Node Herding
arXiv:2512.09947v1 Announce Type: new
Abstract: Heterogeneous graph neural networks (HGNNs) have demonstrated strong capability in modeling complex semantics across multi-type nodes and relations. However, their scalability to large-scale graphs remains challenging due to structural redundancy and ...