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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.…

AWARE: Audio Watermarking with Adversarial Resistance to Edits

arXiv:2510.17512v1 Announce Type: cross Abstract: Prevailing practice in learning-based audio watermarking is to pursue robustness by expanding the set of simulated distortions during training. However, such surrogates are narrow and prone to overfitting. This paper presents AWARE (Audio Watermarking with…

How Good Are LLMs at Processing Tool Outputs?

arXiv:2510.15955v1 Announce Type: new Abstract: Most realistic task automation problems require large language models (LLMs) to call tools, which often return complex JSON responses. These responses must be further processed to derive the information necessary for task completion. The ability…

A Principled Path to Fitted Distributional Evaluation

arXiv:2506.20048v2 Announce Type: replace-cross Abstract: In reinforcement learning, distributional off-policy evaluation (OPE) focuses on estimating the return distribution of a target policy using offline data collected under a different policy. This work focuses on extending the widely used fitted Q-evaluation…

Fire-EnSF: Wildfire Spread Data Assimilation using Ensemble Score Filter

arXiv:2510.15954v1 Announce Type: new Abstract: As wildfires become increasingly destructive and expensive to control, effective management of active wildfires requires accurate, real-time fire spread predictions. To enhance the forecasting accuracy of active fires, data assimilation plays a vital role by…

WaveNet’s Precision in EEG Classification

arXiv:2510.15947v1 Announce Type: new Abstract: This study introduces a WaveNet-based deep learning model designed to automate the classification of EEG signals into physiological, pathological, artifact, and noise categories. Traditional methods for EEG signal classification, which rely on expert visual review,…