arXiv:2511.17566v1 Announce Type: new Abstract: Root cause analysis in microservice systems typically involves two core tasks: root cause localization (RCL) and failure type identification (FTI). Despite substantial research efforts, conventional diagnostic approaches still face two key challenges. First, these methods…
arXiv:2506.09487v2 Announce Type: replace-cross Abstract: This paper presents a tutorial-style survey and implementation guide of BemaGANv2, an advanced GANbased vocoder designed for high-fidelity and long-term audio generation. Long-term audio generation is critical for applications in Text-to-Music (TTM) and Text-to-Audio (TTA)…
arXiv:2511.17582v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, DoRA, and HiRA, enable lightweight adaptation of large pre-trained models via low-rank updates. However, existing PEFT approaches apply static, input-agnostic updates to all tokens, disregarding the varying importance…
arXiv:2511.07280v3 Announce Type: replace-cross Abstract: Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility,…
arXiv:2511.17583v1 Announce Type: new Abstract: Flow Matching has limited ability in achieving one-step generation due to its reliance on learned curved trajectories. Previous studies have attempted to address this limitation by either modifying the coupling distribution to prevent interpolant intersections…
arXiv:2511.18651v1 Announce Type: cross Abstract: This paper introduces Lean 5.0, a human-centric evolution of Lean-Digital integration that connects predictive analytics, AI collaboration, and continuous learning within Industry 5.0 and Construction 5.0 contexts. A systematic literature review (2019-2024) and a 12-week…
arXiv:2511.17584v1 Announce Type: new Abstract: Anomaly detection on attributed graphs plays an essential role in applications such as fraud detection, intrusion monitoring, and misinformation analysis. However, text-attributed graphs (TAGs), in which node information is expressed in natural language, remain underexplored,…
arXiv:2511.19187v1 Announce Type: cross Abstract: Detecting deepfake images is crucial in combating misinformation. We present a lightweight, generalizable binary classification model based on EfficientNet-B6, fine-tuned with transformation techniques to address severe class imbalances. By leveraging robust preprocessing, oversampling, and optimization…
arXiv:2511.17585v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) seeks to understand human emotions by integrating textual, acoustic, and visual signals. Although multimodal fusion is designed to leverage cross-modal complementarity, real-world scenarios often exhibit modality competition: dominant modalities tend to…
arXiv:2410.14581v4 Announce Type: replace Abstract: Attention mechanisms have revolutionized several domains of artificial intelligence, such as natural language processing and computer vision, by enabling models to selectively focus on relevant parts of the input data. While recent work has characterized…
