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arXiv:2602.02020v1 Announce Type: new Abstract: We establish a theoretical connection between wavelet transforms and spiking neural networks through scale-space theory. We rely on the scale-covariant...
arXiv:2602.02023v1 Announce Type: new Abstract: In traditional visual analysis, brushing and linking is commonly used to visually connect multiple views using highlighting techniques. However, brushing...
arXiv:2602.02024v1 Announce Type: new Abstract: A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items...
arXiv:2602.02025v1 Announce Type: new Abstract: Machine learning models depend critically on feature quality, yet useful features are often scattered across multiple relational tables. Feature augmentation...
arXiv:2602.02026v1 Announce Type: new Abstract: We introduce a unified framework for gentle robotic grasping that synergistically couples real-time friction estimation with adaptive grasp control. We...
arXiv:2602.02027v1 Announce Type: new Abstract: The safety of large language models (LLMs) has increasingly emerged as a fundamental aspect of their development. Existing safety alignment...
arXiv:2602.02028v1 Announce Type: new Abstract: Enabling artificial intelligence systems, particularly large language models, to integrate new knowledge and flexibly apply it during reasoning remains a...
arXiv:2602.02029v1 Announce Type: new Abstract: Automatically formulating optimization models from natural language descriptions is a growing focus in operations research, yet current LLM-based approaches struggle...
arXiv:2602.02033v1 Announce Type: new Abstract: Advertising image generation has increasingly focused on online metrics like Click-Through Rate (CTR), yet existing approaches adopt a ``one-size-fits-all" strategy...
arXiv:2602.02034v1 Announce Type: new Abstract: Large language model (LLM)-based agents are increasingly used to perform complex, multi-step workflows in regulated settings such as compliance and...
arXiv:2602.02035v1 Announce Type: new Abstract: Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significantly impact coordination effectiveness. We present...
arXiv:2602.02038v1 Announce Type: new Abstract: Accurately handling contact with friction remains a core bottleneck for Material Point Method (MPM), from reliable contact point detection to...
arXiv:2602.02039v1 Announce Type: new Abstract: The agency expected of Agentic Large Language Models goes beyond answering correctly, requiring autonomy to set goals and decide what...
arXiv:2602.02043v1 Announce Type: new Abstract: Modern Vision-Language Models (VLMs) exhibit a critical flaw in compositional reasoning, often confusing "a red cube and a blue sphere"...
arXiv:2602.02044v1 Announce Type: new Abstract: The increasing availability of relational data has contributed to a growing reliance on network-based representations of complex systems. Over time,...
arXiv:2602.02045v1 Announce Type: new Abstract: Diffusion models have recently emerged as powerful learned priors for Bayesian inverse problems (BIPs). Diffusion-based solvers rely on a presumed...
arXiv:2602.02047v1 Announce Type: new Abstract: Training large language models using 4-bit arithmetic enhances throughput and memory efficiency. Yet, the limited dynamic range of FP4 increases...
arXiv:2602.02048v1 Announce Type: new Abstract: The application of generative artificial intelligence in Creativity Support Tools (CSTs) presents the challenge of interfacing two black boxes: the...
arXiv:2602.02050v1 Announce Type: new Abstract: Tool-using agents based on Large Language Models (LLMs) excel in tasks such as mathematical reasoning and multi-hop question answering. However,...
arXiv:2602.02051v1 Announce Type: new Abstract: Text-to-image diffusion models have revolutionized generative AI, enabling high-quality and photorealistic image synthesis. However, their practical deployment remains hindered by...
arXiv:2602.02052v1 Announce Type: new Abstract: We consider the scattering of time-harmonic plane waves by a compactly supported inhomogeneous scattering obstacle governed by the Helmholtz equation....
arXiv:2602.02053v1 Announce Type: new Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) organizes external knowledge as a hierarchical graph, enabling efficient retrieval and aggregation of scattered evidence across...
arXiv:2602.02055v1 Announce Type: new Abstract: In Internet-of-Things systems, federated learning has advanced online reinforcement learning (RL) by enabling parallel policy training without sharing raw data....
arXiv:2602.02056v1 Announce Type: new Abstract: Ultrafast online learning is essential for high-frequency systems, such as controls for quantum computing and nuclear fusion, where adaptation must...