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arXiv:2601.18570v1 Announce Type: new Abstract: Federated recommendation provides a privacy-preserving solution for training recommender systems without centralizing user interactions. However, existing methods follow an ID-indexed...
arXiv:2601.18572v1 Announce Type: new Abstract: Personalization of LLMs by sociodemographic subgroup often improves user experience, but can also introduce or amplify biases and unfair outcomes...
arXiv:2601.18573v1 Announce Type: new Abstract: In the fundamental Stable Marriage and Stable Roommates problems, there are inherent trade-offs between the size and stability of solutions....
arXiv:2601.18575v1 Announce Type: new Abstract: Solving time-dependent partial differential equations (PDEs) that exhibit sharp gradients or local singularities is computationally demanding, as traditional physics-informed neural...
arXiv:2601.18577v1 Announce Type: new Abstract: Modern video generators still struggle with complex physical dynamics, often falling short of physical realism. Existing approaches address this using...
arXiv:2601.18579v1 Announce Type: new Abstract: Existing Graph RAG methods aiming for insightful retrieval on corpus graphs typically rely on time-intensive processes that interleave Large Language...
arXiv:2601.18580v1 Announce Type: new Abstract: Parallelization in Reinforcement Learning is typically employed to speed up the training of a single policy, where multiple workers collect...
arXiv:2601.18582v1 Announce Type: new Abstract: Personality detection aims to measure an individual's corresponding personality traits through their social media posts. The advancements in Large Language...
arXiv:2601.18585v1 Announce Type: new Abstract: Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapters that capture diverse...
arXiv:2601.18586v1 Announce Type: new Abstract: Climate change is expected to intensify rainfall and other hazards, increasing disruptions in urban transportation systems. Designing effective adaptation strategies...
arXiv:2601.18588v1 Announce Type: new Abstract: Training stability is typically regarded as a prerequisite for reliable optimization in large language models. In this work, we analyze...
arXiv:2601.18589v1 Announce Type: new Abstract: In this paper, we introduce an Adaptive Graph Signal Processing with Dynamic Semantic Alignment (AGSP DSA) framework to perform robust...
arXiv:2601.18590v1 Announce Type: new Abstract: The Gilbert--Varshamov (GV) bound is a central benchmark in coding theory, establishing existential guarantees for error-correcting codes and serving as...
arXiv:2601.18591v1 Announce Type: new Abstract: Machine Learning (ML) Operations (MLOps) frameworks have been conceived to support developers and AI engineers in managing the lifecycle of...
arXiv:2601.18595v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated impressive formal reasoning abilities, they often break down when problems require complex proof...
arXiv:2601.18597v1 Announce Type: new Abstract: Real-time small object detection in Unmanned Aerial Vehicle (UAV) imagery remains challenging due to limited feature representation and ineffective multi-scale...
arXiv:2601.18604v2 Announce Type: new Abstract: Motivation: Pathway enrichment analysis is widely used to interpret gene expression data. Standard approaches, such as GSEA, rely on predefined...
arXiv:2601.18608v1 Announce Type: new Abstract: Shapley values have emerged as a central game-theoretic tool in explainable AI (XAI). However, computing Shapley values exactly requires $2^d$...
arXiv:2601.18612v1 Announce Type: new Abstract: The canonical challenge of entity resolution within high-compliance sectors, where secure identity reconciliation is frequently confounded by significant data heterogeneity,...
arXiv:2601.18615v1 Announce Type: new Abstract: This paper proposes a data-driven model for solving the inverse problem of electrocardiography, the mathematical problem that forms the basis...
arXiv:2601.18616v1 Announce Type: new Abstract: Objectives. Major research and implementation efforts have been devoted to indexing articles according to the major topics discussed, but much...
arXiv:2601.18617v1 Announce Type: new Abstract: During language acquisition, children successively learn to categorize phonemes, identify words, and combine them with syntax to form new meaning....
arXiv:2601.18619v1 Announce Type: new Abstract: Self-supervised learning (SSL) has emerged as a powerful strategy for representation learning under limited annotation regimes, yet its effectiveness remains...
arXiv:2601.18620v1 Announce Type: new Abstract: Building world models is essential for planning in real-world domains such as businesses. Since such domains have rich semantics, we...