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arXiv:2601.17089v1 Announce Type: new Abstract: In recent years, Multimodal Large Language Models (MLLMs) have made significant progress in visual question answering tasks. However, directly applying...
arXiv:2601.17090v1 Announce Type: new Abstract: Partial differential equations (PDEs) govern complex systems, yet neural operators often struggle to efficiently capture the long-range, nonlocal interactions inherent...
arXiv:2601.17091v1 Announce Type: new Abstract: ROCKET (RandOm Convolutional KErnel Transform) is a feature extraction algorithm created for Time Series Classification (TSC), published in 2019. It...
arXiv:2601.17093v1 Announce Type: new Abstract: Comparing neural network representations is essential for understanding and validating models in scientific applications. Existing methods, however, often provide a...
arXiv:2601.17094v1 Announce Type: new Abstract: Large Language Models (LLMs) generate fluent text, yet whether they truly understand the world or merely produce plausible language about...
arXiv:2601.17095v1 Announce Type: new Abstract: For architectural design, representation across multiple Levels of Details (LoD) is essential for achieving a smooth transition from conceptual massing...
arXiv:2601.17096v1 Announce Type: new Abstract: Recent scholarship typically characterizes Large Language Models (LLMs) through either an \textit{Instrumental Paradigm} (viewing models as reflections of their developers'...
arXiv:2601.17097v1 Announce Type: new Abstract: Real-time automatic speech recognition systems are increasingly integrated into interactive applications, from voice assistants to live transcription services. However, scaling...
arXiv:2601.17107v1 Announce Type: new Abstract: Annotating medical data for training AI models is often costly and limited due to the shortage of specialists with relevant...
arXiv:2601.17108v1 Announce Type: new Abstract: This paper proposes a Mamba-assisted neural network framework incorporating self-attention mechanism to achieve improved channel estimation with low complexity for...
arXiv:2601.17110v1 Announce Type: new Abstract: Accurate short-term energy consumption forecasting is essential for efficient power grid management, resource allocation, and market stability. Traditional time-series models...
arXiv:2601.17111v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are typically pre-trained with explicit load-balancing constraints to ensure statistically balanced expert routing. Despite this, we observe...
arXiv:2601.17112v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse natural language tasks but suffer from extremely large memory footprints...
arXiv:2601.17123v1 Announce Type: new Abstract: We introduce and explore a new multimodal input representation for vision-language models: acoustic field video. Unlike conventional video (RGB with...
arXiv:2601.17124v2 Announce Type: new Abstract: The field of image generation is currently bifurcated into autoregressive (AR) models operating on discrete tokens and diffusion models utilizing...
arXiv:2601.17130v1 Announce Type: new Abstract: Graph neural networks (GNNs) have become the standard tool for encoding data and their complex relationships into continuous representations, improving...
arXiv:2601.17131v1 Announce Type: new Abstract: Subgame solving is a technique for scaling algorithms to large games by locally refining a precomputed blueprint strategy during gameplay....
arXiv:2601.17132v1 Announce Type: new Abstract: Few forces rival fear in their ability to mobilize societies, distort communication, and reshape collective behavior. In computational linguistics, fear...
arXiv:2601.17133v1 Announce Type: new Abstract: Fine-tuning Large Language Models (LLMs) for specialized domains is constrained by a fundamental challenge: the need for diverse, cross-organizational data...
arXiv:2601.17134v1 Announce Type: new Abstract: Understanding and modeling consumers' stylistic taste such as "sporty" is crucial for creating designs that truly connect with target audiences....
arXiv:2601.17135v1 Announce Type: new Abstract: Imitation learning enables robots to acquire complex manipulation skills from human demonstrations, but current methods rely solely on low-level sensorimotor...
arXiv:2601.17136v1 Announce Type: new Abstract: Clustering is an important tool in data analysis, with K-means being popular for its simplicity and versatility. However, it cannot...
arXiv:2601.17139v1 Announce Type: new Abstract: Civil society has been deemed by various scholars, such as Robert D. Putnam, to be a predictor and a cornerstone...
arXiv:2601.17149v1 Announce Type: new Abstract: The interactions between the brain and heart during sleep are responsible for regulating autonomic function. While brain-heart coupling has been...