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arXiv:2601.09150v4 Announce Type: replace Abstract: Large Language Models (LLMs) motivate generative agent simulation (e.g., AI Town) to create a ``dynamic world'', holding immense value across...
arXiv:2601.09828v3 Announce Type: replace Abstract: Effective retrieval across both seen and unseen categories is crucial for modern image retrieval systems. Retrieval on seen categories ensures...
arXiv:2601.09896v2 Announce Type: replace Abstract: Visual generative AI models are trained using a one-size-fits-all measure of aesthetic appeal. However, what is deemed "aesthetic" is inextricably...
arXiv:2601.10485v2 Announce Type: replace Abstract: Domain-specific knowledge graphs (DKGs) are critical yet often suffer from limited coverage compared to General Knowledge Graphs (GKGs). Existing tasks...
arXiv:2601.10498v3 Announce Type: replace Abstract: This note introduces Projected Microbatch Accumulation (PROMA), a proximal policy method that modifies gradient accumulation across microbatches rather than relying...
arXiv:2601.10564v4 Announce Type: replace Abstract: In this paper, we introduce monoidal rewriting systems (MRS), an abstraction of string rewriting in which reductions are defined over...
arXiv:2601.11144v3 Announce Type: replace Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) frameworks face a trade-off between the comprehensiveness of global search and the efficiency of local search....
arXiv:2601.11158v2 Announce Type: replace Abstract: An r-partite graph is an interval r-graph if corresponding to each vertex we can assign an interval of the real...
arXiv:2601.11219v2 Announce Type: replace Abstract: Federated learning (FL) for large language models (LLMs) has attracted increasing attention as a privacy-preserving approach for adapting models over...
arXiv:2601.11471v2 Announce Type: replace Abstract: The key-value (KV) cache is a primary memory bottleneck in Transformers. We propose Low-Rank Key-Value (LRKV) attention, which reduces KV...
arXiv:2601.11479v2 Announce Type: replace Abstract: Ethiopia's Ministry of Health is upgrading health posts to improve access to essential services, particularly in rural areas. Limited resources,...
arXiv:2601.11911v2 Announce Type: replace Abstract: Convolutional neural networks (CNNs) have achieved state-of-the-art performance in image recognition tasks but often involve complex architectures that may overfit...
arXiv:2601.11942v2 Announce Type: replace Abstract: Quantum neural networks (QNNs) have attracted growing interest for scientific machine learning, yet in regression settings they often suffer from...
arXiv:2601.12066v3 Announce Type: replace Abstract: Existing video object removal methods predominantly rely on diffusion models following a noise-to-data paradigm, where generation starts from uninformative Gaussian...
arXiv:2601.12247v2 Announce Type: replace Abstract: Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) approaches. However, current...
arXiv:2601.12448v2 Announce Type: replace Abstract: Time series anomaly detection (TSAD) is essential for ensuring the safety and reliability of aerospace software systems. Although large language...
arXiv:2601.12913v3 Announce Type: replace Abstract: This paper argues that interpretability research in Artificial Intelligence (AI) is fundamentally ill-posed as existing definitions of interpretability fail to...
arXiv:2601.13319v2 Announce Type: replace Abstract: Dialectal Arabic (DA) speech data vary widely in domain coverage, dialect labeling practices, and recording conditions, complicating cross-dataset comparison and...
arXiv:2601.13346v2 Announce Type: replace Abstract: Language Identification (LID) is the task of determining the language of a given text and is a fundamental preprocessing step...
arXiv:2601.13380v2 Announce Type: replace Abstract: Learning in data-scarce settings has recently gained significant attention in the research community. Semi-supervised object detection(SSOD) aims to improve detection...
arXiv:2601.13465v2 Announce Type: replace Abstract: We demonstrate that a single training trajectory can transform a graph neural network into an unsupervised heuristic for combinatorial optimization....
arXiv:2601.13663v2 Announce Type: replace Abstract: The Longest Edge Bisection of a triangle is performed by joining the midpoint of its longest edge to the opposite...
arXiv:2601.14210v2 Announce Type: replace Abstract: LLMs often produce fluent but incorrect answers, yet detecting such hallucinations typically requires multiple sampling passes or post-hoc verification, adding...
arXiv:2601.14652v2 Announce Type: replace Abstract: While multi-agent systems (MAS) promise elevated intelligence through coordination of agents, current approaches to automatic MAS design under-deliver. Such shortcomings...