arXiv:2601.04227v1 Announce Type: new Abstract: Generative audio technologies now enable highly realistic voice cloning and real-time voice conversion, increasing the risk of impersonation, fraud, and misinformation in communication channels such as phone and video calls. This study investigates real-time detection of AI-generated speech produced using Retrieval-based Voice Conversion (RVC), evaluated on the DEEP-VOICE dataset, which includes authentic and voice-converted speech samples from multiple well-known speakers. To simulate realistic conditions, deepfake generation is applied to isolated vocal components, followed […]

Ver mais

arXiv:2601.05403v1 Announce Type: new Abstract: Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-authored corpora, LLMs may inherit a range of human biases. Behavioral biases can lead to instability and uncertainty in decision-making, particularly when processing financial information. However, existing research on LLM bias has mainly focused on direct questioning or simplified, general-purpose settings, with limited consideration of the complex real-world financial environments and high-risk, […]

Ver mais

Multimodal representation learning aims to construct a shared embedding space in which heterogeneous modalities are semantically aligned. Despite strong empirical results, InfoNCE-based objectives introduce inherent conflicts that yield distribution gaps across modalities. In this work, we identify two conflicts in the multimodal regime, both exacerbated as the number of modalities increases: (i) an alignment-uniformity conflict, whereby the repulsion of uniformity undermines pairwise alignment, and (ii) an intra-alignment conflict, where aligning multiple modalities induces competing alignment directions. To address […]

Ver mais

Table of Links Abstract and 1. Introduction Related Work Preliminaries and Notations Differentiable Structural Information 4.1. A New Formulation 4.2. Properties 4.3. Differentiability & Deep Graph Clustering LSEnet 5.1. Embedding Leaf Nodes 5.2. Learning Parent Nodes 5.3. Hyperbolic Partitioning Tree Experiments 6.1. Graph Clustering 6.2. Discussion on Structural Entropy Conclusion, Broader Impact, and References Appendix A. Proofs B. Hyperbolic Space C. Technical Details D. Additional Results 4. Differentiable Structural Information In this section, we first establish a new […]

Ver mais

Accurate prediction of pedestrian intention and future paths is essential for traffic safety, urban planning, and autonomous navigation. This study develops a multimodal prediction model that combines meaning-based image-text features, motion trajectories, and social interactions. We extract visual-language information from RGB sequences using a CLIP-based encoder and represent group behavior using a Social-GRU network. To improve the reliability of predictions, we apply Bayesian modeling to manage uncertainty. We tested the method on the Waymo and ETH/UCY datasets. On […]

Ver mais

The limitations of classical computing in solving complex problems in cryptography, materials science, and optimization necessitate the development of a new computational paradigm based on the principles of quantum mechanics. This article aims to analyse the current state of quantum computing hardware, evaluate the primary challenges to achieving fault tolerance, and project a realistic timeline for its practical application. The methodology involves a systematic review and comparative analysis of publicly available empirical data from peer-reviewed literature and corporate […]

Ver mais