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arXiv:2602.19048v1 Announce Type: new Abstract: Immersive videos (IVs) provide 360{\deg} environments that create a strong sense of presence and spatial exploration. Unlike traditional videos, IVs...
arXiv:2602.19049v1 Announce Type: new Abstract: Large language models increasingly rely on long chains of thought to improve accuracy, yet such gains come with substantial inference-time...
arXiv:2602.19053v1 Announce Type: new Abstract: Self-supervised feed-forward methods for scene flow estimation offer real-time efficiency, but their supervision from two-frame point correspondences is unreliable and...
arXiv:2602.19058v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have rapidly advanced across various domains, yet they still lag behind strong text-only large language models...
arXiv:2602.19062v1 Announce Type: new Abstract: Path planning for high-speed unmanned surface vehicles requires more complex solutions to reduce sailing time and save energy. This article...
arXiv:2602.19063v1 Announce Type: new Abstract: 3D large multimodal models (3D LMMs) rely heavily on ego poses for enabling directional question-answering and spatial reasoning. However, most...
arXiv:2602.19064v1 Announce Type: new Abstract: Range-view (RV) based LiDAR diffusion has recently made huge strides towards 2D photo-realism. However, it neglects 3D geometry realism and...
arXiv:2602.19065v1 Announce Type: new Abstract: Large Language Models (LLMs) are evolving into autonomous agents, yet current "frameless" development--relying on ambiguous natural language without engineering blueprints--leads...
arXiv:2602.19066v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) have recently achieved strong results in text generation. However, their multi-step sampling leads to slow inference,...
arXiv:2602.19068v1 Announce Type: new Abstract: Current time series foundation models (TSFMs) primarily focus on learning prevalent and regular patterns within a predefined time or frequency...
arXiv:2602.19069v1 Announce Type: new Abstract: Recent years have witnessed tremendous progress in enabling LLMs to solve complex reasoning tasks such as math and coding. As...
arXiv:2602.19070v1 Announce Type: new Abstract: This work proposes a novel cooperative transportation framework for multi-agent systems that does not require any prior knowledge of cargo...
arXiv:2602.19071v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) has become popular in the last few years. The Artificial Intelligence (AI) community in general, and...
arXiv:2602.19073v1 Announce Type: new Abstract: Over the past three years, the financial services industry has witnessed Large Language Models (LLMs) and agents transitioning from the...
arXiv:2602.19079v1 Announce Type: new Abstract: Topic modeling extracts latent themes from large text collections, but leading approaches like BERTopic face critical limitations: stochastic instability, loss...
arXiv:2602.19083v1 Announce Type: new Abstract: The advent of one-step text-to-image (T2I) models offers unprecedented synthesis speed. However, their application to text-guided image editing remains severely...
arXiv:2602.19084v1 Announce Type: new Abstract: UCX is a communication framework that enables low-latency, high-bandwidth communication in HPC systems. With its unified API, UCX facilitates efficient...
arXiv:2602.19085v1 Announce Type: new Abstract: The transition to auto-bidding in online advertising has shifted the focus of auction theory from quasi-linear utility maximization to value...
arXiv:2602.19086v1 Announce Type: new Abstract: Kuzushiji was one of the most popular writing styles in pre-modern Japan and was widely used in both personal letters...
arXiv:2602.19087v1 Announce Type: new Abstract: The critical need for transparent and trustworthy machine learning in cybersecurity operations drives the development of this integrated Explainable AI...
arXiv:2602.19088v1 Announce Type: new Abstract: Today's distributed systems operate in complex environments that inevitably involve faults and even adversarial behaviors. Predicting their performance under such...
arXiv:2602.19089v1 Announce Type: new Abstract: Current 3D human animation methods struggle to achieve photorealism: kinematics-based approaches lack non-rigid dynamics (e.g., clothing dynamics), while methods that...
arXiv:2602.19090v1 Announce Type: new Abstract: In this paper, we discuss numerical methods for the eigenvalue decomposition of real symmetric matrices. While many existing methods can...
arXiv:2602.19091v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable success in comprehension tasks such as visual description and visual question answering....