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arXiv:2601.04568v2 Announce Type: replace Abstract: Retrieval Augmented Generation (RAG) has made significant strides in overcoming key limitations of large language models, such as hallucination, lack...
arXiv:2601.05280v2 Announce Type: replace Abstract: We formalise recursive self-training in Large Language Models (LLMs) and Generative AI as a discrete-time dynamical system. We prove that...
arXiv:2601.05500v3 Announce Type: replace Abstract: Benchmarking the relative capabilities of AI systems, including Large Language Models (LLMs) and Vision Models, typically ignores the impact of...
arXiv:2601.06391v2 Announce Type: replace Abstract: In this paper, we introduce Object-WIPER, a training-free framework for removing dynamic objects and their associated visual effects from videos,...
arXiv:2601.06412v2 Announce Type: replace Abstract: The United States-China rivalry has placed frontier dual-use technologies, particularly Artificial Intelligence (AI), at the center of global power dynamics,...
arXiv:2601.06932v3 Announce Type: replace Abstract: Linking names across historical sources, languages, and writing systems remains a fundamental challenge in digital humanities and geographic information retrieval....
arXiv:2601.08549v3 Announce Type: replace Abstract: We introduce a two-stage multitask learning framework for analyzing Electroencephalography (EEG) signals that integrates denoising, dynamical modeling, and representation learning....
arXiv:2601.09329v2 Announce Type: replace Abstract: We propose a Gaussian random coding scheme for AR($p$) Gaussian channels that generalizes the celebrated Schalkwijk-Kailath (SK) coding scheme. This...
arXiv:2601.11036v3 Announce Type: replace Abstract: Quality of Service (QoS) prediction is one of the most fundamental problems in service computing and personalized recommendation. In the...
arXiv:2601.11231v2 Announce Type: replace Abstract: We consider the problem of adaptively monitoring a wildfire front using a mobile agent (e.g., a drone), whose trajectory determines...
arXiv:2601.13040v2 Announce Type: replace Abstract: While transistor density is still increasing, clock speeds are not, motivating the search for new parallel architectures. One approach is...
arXiv:2601.13372v3 Announce Type: replace Abstract: Despite being regarded as a significant step toward regulating Artificial Intelligence (AI) systems and its emphasis on fundamental rights, the...
arXiv:2601.13851v2 Announce Type: replace Abstract: Self-Organizing Maps (SOMs) provide topology-preserving projections of high-dimensional data, yet their use as generative models remains largely unexplored. We show...
arXiv:2601.14252v3 Announce Type: replace Abstract: We study zero-error class identification under constrained observations with three resources: tag rate $L$ (bits per entity), identification cost $W$...
arXiv:2601.14706v2 Announce Type: replace Abstract: In this paper, we present LookBench (We use the term "look" to reflect retrieval that mirrors how people shop --...
arXiv:2601.15599v3 Announce Type: replace Abstract: Modern business environments demand continuous reconfiguration of cross-functional processes, yet most enterprise systems remain organized around siloed departments, rigid workflows,...
arXiv:2601.16210v2 Announce Type: replace Abstract: Discrete video VAEs underpin modern text-to-video generation and video understanding systems, yet existing tokenizers typically learn visual codebooks at a...
arXiv:2601.16449v2 Announce Type: replace Abstract: Understanding human emotions from multimodal signals poses a significant challenge in affective computing and human-robot interaction. While multimodal large language...
arXiv:2601.17074v2 Announce Type: replace Abstract: The accurate estimation of Arctic snow depth remains a critical time-varying inverse problem due to the extreme scarcity and noise...
arXiv:2601.17258v2 Announce Type: replace Abstract: Video Anomaly Understanding (VAU) is a novel task focused on describing unusual occurrences in videos. Despite growing interest, the evaluation...
arXiv:2601.17336v2 Announce Type: replace Abstract: Automated Kellgren--Lawrence (KL) grading from knee radiographs is challenging due to subtle structural changes, long-range anatomical dependencies, and ambiguity near...
arXiv:2601.17354v3 Announce Type: replace Abstract: Efficient and high-fidelity 3D scene modeling is a long-standing pursuit in computer graphics. While recent 3D Gaussian Splatting (3DGS) methods...
arXiv:2601.17508v2 Announce Type: replace Abstract: We consider the permanent of a square matrix with non-negative entries. A tractable approximation is given by the so-called Bethe...
arXiv:2601.18467v2 Announce Type: replace Abstract: Deep research agents have shown remarkable potential in handling long-horizon tasks. However, state-of-the-art performance typically relies on online reinforcement learning...