Archives AI News

The Moral Foundations Reddit Corpus

arXiv:2208.05545v3 Announce Type: replace-cross Abstract: Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used to detect moral…

Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

arXiv:2510.15961v1 Announce Type: new Abstract: Illicit drug use among teenagers and young adults (TYAs) remains a pressing public health concern, with rising prevalence and long-term impacts on health and well-being. To detect illicit drug use among TYAs, researchers analyze large-scale…

VERINA: Benchmarking Verifiable Code Generation

arXiv:2505.23135v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly integrated in software development, but ensuring correctness in LLM-generated code remains challenging and often requires costly manual review. Verifiable code generation — jointly generating code, specifications, and proofs of…

UniCrossFi: A Unified Framework For Cross-Domain Wi-Fi-based Gesture Recognition

arXiv:2310.06328v4 Announce Type: replace Abstract: Wi-Fi sensing systems are severely hindered by cross domain problem when deployed in unseen real-world environments. Existing methods typically design separate frameworks for either domain adaptation or domain generalization, often relying on extensive labeled data.…

Bayesian Computation in Deep Learning

arXiv:2502.18300v4 Announce Type: replace Abstract: Bayesian methods have shown success in deep learning applications. For example, in predictive tasks, Bayesian neural networks leverage Bayesian reasoning of model uncertainty to improve the reliability and uncertainty awareness of deep neural networks. In…

One-step Diffusion Models with Bregman Density Ratio Matching

arXiv:2510.16983v1 Announce Type: cross Abstract: Diffusion and flow models achieve high generative quality but remain computationally expensive due to slow multi-step sampling. Distillation methods accelerate them by training fast student generators, yet most existing objectives lack a unified theoretical foundation.…