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arXiv:2507.21989v2 Announce Type: replace Abstract: Advances in embedding models for text, image, audio, and video drive progress across multiple domains, including retrieval-augmented generation, recommendation systems,...
arXiv:2508.00776v2 Announce Type: replace Abstract: We show for several computational problems how classical greedy algorithms for special cases can be derived in a simple way...
arXiv:2508.01617v2 Announce Type: replace Abstract: Autoregressive models (ARMs) have long dominated the landscape of biomedical vision-language models (VLMs). Recently, masked diffusion models such as LLaDA...
arXiv:2508.04605v4 Announce Type: replace Abstract: We propose a framework for learning maps between probability distributions that broadly generalizes the time dynamics of flow and diffusion...
arXiv:2508.05282v4 Announce Type: replace Abstract: While Chain-of-Thought (CoT) prompting empowers Large Language Models (LLMs), ensuring reasoning reliability remains an open challenge. Contrary to the prevailing...
arXiv:2508.07667v3 Announce Type: replace Abstract: Addressing contextual privacy concerns remains challenging in interactive settings where large language models (LLMs) process information from multiple sources (e.g.,...
arXiv:2508.08337v2 Announce Type: replace Abstract: Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibility into unfairness as...
arXiv:2508.09888v2 Announce Type: replace Abstract: In the field of pedometrics, tabular machine learning is the predominant method for soil property prediction from remote and proximal...
arXiv:2508.13397v2 Announce Type: replace Abstract: Large inter-GPU all-reduce operations, prevalent throughout deep learning, are bottlenecked by communication costs. Emerging heterogeneous architectures are comprised of complex...
arXiv:2508.15427v2 Announce Type: replace Abstract: Automating pallet handling in outdoor logistics and construction environments remains challenging due to unstructured scenes, variable pallet configurations, and changing...
arXiv:2508.16069v3 Announce Type: replace Abstract: Recent advances in point cloud object detection have increasingly adopted Transformer-based and State Space Models (SSMs) to capture long-range dependencies....
arXiv:2508.19982v4 Announce Type: replace Abstract: Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and flexible token...
arXiv:2508.21112v5 Announce Type: replace Abstract: The human ability to seamlessly perform multimodal reasoning and physical interaction in the open world is a core goal for...
arXiv:2508.21421v3 Announce Type: replace Abstract: Fine-tuning pretrained models has become a standard pathway to achieve state-of-the-art performance across a wide range of domains, leading to...
arXiv:2508.21438v2 Announce Type: replace Abstract: The development of continuous biomanufacturing processes requires robust and early anomaly detection, since even minor deviations can compromise yield and...
arXiv:2509.01350v3 Announce Type: replace Abstract: Effective specification-aware part retrieval within complex CAD assemblies is essential for automated engineering tasks. However, using LLMs/VLMs for this task...
arXiv:2509.01552v2 Announce Type: replace Abstract: Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding tasks. However, the increasing demand for high-resolution image and...
arXiv:2509.02452v3 Announce Type: replace Abstract: Do LLMs genuinely incorporate external definitions, or do they primarily rely on their parametric knowledge? To address these questions, we...
arXiv:2509.03481v2 Announce Type: replace Abstract: Combinatorial group testing reduces screening costs and turnaround time but remains challenging to apply due to design complexity, varying applicability,...
arXiv:2509.04625v2 Announce Type: replace Abstract: The rapid adoption of 5G New Radio (NR), particularly in the millimeter-wave (mmWave) spectrum, imposes stringent demands on the flexibility,...
arXiv:2509.07477v2 Announce Type: replace Abstract: Deep neural networks excel in radiological image classification but frequently suffer from poor interpretability, limiting clinical acceptance. We present MedicalPatchNet,...
arXiv:2509.08747v2 Announce Type: replace Abstract: Semi-structured (2:4) sparsity is a widely adopted pruning method in modern hardware and software ecosystems (e.g., NVIDIA Sparse Tensor Cores...
arXiv:2509.08976v2 Announce Type: replace Abstract: Cyber warfare has become a central element of modern conflict, especially within multi-domain operations. As both a distinct and critical...
arXiv:2509.11098v2 Announce Type: replace Abstract: AI-driven recommender systems are often perceived as personalization black boxes, limiting users' ability to understand how their data shapes content...