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arXiv:2602.17454v1 Announce Type: new Abstract: Differential privacy (DP) implementations are notoriously prone to errors, with subtle bugs frequently invalidating theoretical guarantees. Existing verification methods are...
arXiv:2602.17458v1 Announce Type: new Abstract: Despite the high volume of open-source Cyber Threat Intelligence (CTI), our understanding of long-term threat actor-victim dynamics remains fragmented due...
arXiv:2602.17465v1 Announce Type: new Abstract: Modern language models (LMs) increasingly require two critical resources: computational resources and data resources. Data selection techniques can effectively reduce...
arXiv:2602.17467v1 Announce Type: new Abstract: The increasing volume of hate speech on online platforms poses significant societal challenges. While the Natural Language Processing community has...
arXiv:2602.17469v1 Announce Type: new Abstract: The core theme of bidirectional alignment is ensuring that AI systems accurately understand human intent and that humans can trust...
arXiv:2602.17472v1 Announce Type: new Abstract: Recent advances in automated vehicles have focused on improving perception performance under adverse weather conditions; however, research on physical hardware...
arXiv:2602.17473v1 Announce Type: new Abstract: Reconstructing deformable surgical scenes from endoscopic videos is challenging and clinically important. Recent state-of-the-art methods based on implicit neural representations...
arXiv:2602.17474v1 Announce Type: new Abstract: Electro-Ribbon Actuators (ERAs) are lightweight flexural actuators that exhibit ultrahigh displacement and fast movement. However, their embedded sensing relies on...
arXiv:2602.17475v1 Announce Type: new Abstract: Large Language Models (LLMs) consistently excel in diverse medical Natural Language Processing (NLP) tasks, yet their substantial computational requirements often...
arXiv:2602.17477v1 Announce Type: new Abstract: Deep generative models such as flow matching and diffusion models have shown great potential in learning complex distributions and dynamical...
arXiv:2602.17478v1 Announce Type: new Abstract: Characterizing two-dimensional quantum materials from optical microscopy images is challenging due to the subtle layer-dependent contrast, limited labeled data, and...
arXiv:2602.17480v1 Announce Type: new Abstract: In recent years, Homotopy Type Theory (HoTT) has had great success both as a foundation of mathematics and as internal...
arXiv:2602.17481v1 Announce Type: new Abstract: Augmented Reality (AR) can simulate various visual perceptions, such as how individuals with colorblindness see the world. However, these simulations...
arXiv:2602.17482v1 Announce Type: new Abstract: We present an algorithm turning any term of a linear quantum $\lambda$-calculus into a quantum circuit. The essential ingredient behind...
arXiv:2602.17483v1 Announce Type: new Abstract: Large language models (LLMs), and conversational agents based on them, are exposed to personal data (PD) during pre-training and during...
arXiv:2602.17484v1 Announce Type: new Abstract: Image Copy Detection (ICD) aims to identify manipulated content between image pairs through robust feature representation learning. While self-supervised learning...
arXiv:2602.17486v1 Announce Type: new Abstract: Feedback delays are inevitable in real-world multi-agent learning. They are known to severely degrade performance, and the convergence rate under...
arXiv:2602.17488v1 Announce Type: new Abstract: We study the problem of differentially private (DP) computation of coreset for the $k$-means objective. For a given input set...
arXiv:2602.17490v1 Announce Type: new Abstract: Coin selection refers to the problem of choosing a set of tokens to fund a transaction in token-based payment systems...
arXiv:2602.17492v1 Announce Type: new Abstract: A general model is formulated for elasto-plastic materials undergoing linear kinematic hardening to describe microstructure evolution associated with phase transformations....
arXiv:2602.17493v1 Announce Type: new Abstract: We develop a method for training neural networks on Boolean data in which the values at all nodes are strictly...
arXiv:2602.17494v1 Announce Type: new Abstract: The TV-Stokes model is a two-step variational method for image denoising that combines the estimation of a divergence-free tangent field...
arXiv:2602.17497v1 Announce Type: new Abstract: Learning from self-sampled data and sparse environmental feedback remains a fundamental challenge in training self-evolving agents. Temporal credit assignment mitigates...
arXiv:2602.17498v1 Announce Type: new Abstract: Natural Language Processing (NLP) tools support requirements engineering (RE) tasks like requirements elicitation, classification, and validation. However, they are often...