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arXiv:2602.15698v1 Announce Type: new Abstract: As artificial intelligence (AI) increasingly integrates into crowdfunding practices, strategic disclosure of AI involvement has become critical. Yet, empirical insights...
arXiv:2602.15702v1 Announce Type: new Abstract: Given two matroids $\mathcal{M}_1$ and $\mathcal{M}_2$ over the same ground set, the matroid intersection problem is to find the maximum...
arXiv:2602.15704v1 Announce Type: new Abstract: Learning dynamical systems through purely data-driven methods is challenging as they do not learn the underlying conservation laws that enable...
arXiv:2602.15705v1 Announce Type: new Abstract: Database-driven cognitive radio networks (DB-CRNs) enable dynamic spectrum sharing through geolocation databases but introduce critical security and privacy challenges, including...
arXiv:2602.15707v1 Announce Type: new Abstract: Real-time conversational assistants for procedural tasks often depend on video input, which can be computationally expensive and compromise user privacy....
arXiv:2602.15708v1 Announce Type: new Abstract: An ordinal preference domain is a subset of preference orders that the voters are allowed to cast in an election....
arXiv:2602.15711v1 Announce Type: new Abstract: Node embeddings map graph vertices into low-dimensional Euclidean spaces while preserving structural information. They are central to tasks such as...
arXiv:2602.15712v1 Announce Type: new Abstract: Across the natural and life sciences, images have become a primary measurement modality, yet the dominant analytic paradigm remains semantics-first....
arXiv:2602.15716v1 Announce Type: new Abstract: Lexical semantic change detection (LSCD) increasingly relies on contextualised language model embeddings, yet most approaches still quantify change using a...
arXiv:2602.15720v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved remarkable success across various vision tasks, yet their deployment is often hindered by prohibitive computational...
arXiv:2602.15721v1 Announce Type: new Abstract: We present Lifelong Scalable Multi-Agent Realistic Testbed (LSMART), an open-source simulator to evaluate any Multi-Agent Path Finding (MAPF) algorithm in...
arXiv:2602.15724v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions and navigate through previously unseen environments. Recent approaches increasingly employ...
arXiv:2602.15725v1 Announce Type: new Abstract: Large language models achieve strong performance on many complex reasoning tasks, yet their accuracy degrades sharply on benchmarks that require...
arXiv:2602.15727v1 Announce Type: new Abstract: Visual analogy learning enables image manipulation through demonstration rather than textual description, allowing users to specify complex transformations difficult to...
arXiv:2602.15730v1 Announce Type: new Abstract: Understanding the causal effects of text on downstream outcomes is a central task in many applications. Estimating such effects requires...
arXiv:2602.15734v1 Announce Type: new Abstract: Existing 3D open-vocabulary scene understanding methods mostly emphasize distilling language features from 2D foundation models into 3D feature fields, but...
arXiv:2602.15736v1 Announce Type: new Abstract: Identifying influential nodes and edges in directed networks remains a fundamental challenge across domains from social influence to biological regulation....
arXiv:2602.15738v1 Announce Type: new Abstract: Integrating human expertise into machine learning systems often reduces the role of experts to labeling oracles, a paradigm that limits...
arXiv:2602.15739v1 Announce Type: new Abstract: The Partially Ordered Workflow Language (POWL) has recently emerged as a process modeling notation, offering strong quality guarantees and high...
arXiv:2602.15740v1 Announce Type: new Abstract: Alzheimer's disease (AD) is a progressive neurodegenerative condition necessitating early and precise diagnosis to provide prompt clinical management. Given the...
arXiv:2602.15745v1 Announce Type: new Abstract: Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We...
arXiv:2602.15749v1 Announce Type: new Abstract: Neural autoencoders underpin generative models. Practical, large-scale use of neural autoencoders for generative modeling necessitates fast encoding, low latent rates,...
arXiv:2602.15750v1 Announce Type: new Abstract: Recent advances in urban region representation learning have enabled a wide range of applications in urban analytics, yet existing methods...
arXiv:2602.15752v1 Announce Type: new Abstract: On two-sided matching platforms such as online dating and recruiting, recommendation algorithms often aim to maximize the total number of...