Category
Academic
AI Copyright Infringement: Navigating the Legal Risks of AI-Generated Content
The accelerated growth of generative artificial intelligence (AI) tools that can generate text, images, music, code, and multimodal content has caused a legal and philosophical …
The Rhetoric of Machine Learning
arXiv:2604.06754v1 Announce Type: new Abstract: I examine the technology of machine learning from the perspective of rhetoric, which is simply the art of persuasion. Rather …
Busemann energy-based attention for emotion analysis in Poincar\'e discs
arXiv:2604.06752v1 Announce Type: new Abstract: We present EmBolic - a novel fully hyperbolic deep learning architecture for fine-grained emotion analysis from textual messages. The underlying …
Extraction of linearized models from pre-trained networks via knowledge distillation
arXiv:2604.06732v1 Announce Type: new Abstract: Recent developments in hardware, such as photonic integrated circuits and optical devices, are driving demand for research on constructing machine …
Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach
arXiv:2604.06727v1 Announce Type: new Abstract: Heterogeneity in time series data is more pronounced than in vision or language, as temporal dynamics vary substantially across domains …
Bi-Lipschitz Autoencoder With Injectivity Guarantee
arXiv:2604.06701v1 Announce Type: new Abstract: Autoencoders are widely used for dimensionality reduction, based on the assumption that high-dimensional data lies on low-dimensional manifolds. Regularized autoencoders …
Towards Accurate and Calibrated Classification: Regularizing Cross-Entropy From A Generative Perspective
arXiv:2604.06689v1 Announce Type: new Abstract: Accurate classification requires not only high predictive accuracy but also well-calibrated confidence estimates. Yet, modern deep neural networks (DNNs) are …
GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records
arXiv:2604.06684v1 Announce Type: new Abstract: Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in modern healthcare. While in-context learning (ICL) …
FlowAdam: Implicit Regularization via Geometry-Aware Soft Momentum Injection
arXiv:2604.06652v1 Announce Type: new Abstract: Adaptive moment methods such as Adam use a diagonal, coordinate-wise preconditioner based on exponential moving averages of squared gradients. This …
SHAPE: Stage-aware Hierarchical Advantage via Potential Estimation for LLM Reasoning
arXiv:2604.06636v1 Announce Type: new Abstract: Process supervision has emerged as a promising approach for enhancing LLM reasoning, yet existing methods fail to distinguish meaningful progress …
SubFLOT: Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport
arXiv:2604.06631v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training while preserving data privacy, but its practical deployment is hampered by system and …