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arXiv:2602.02731v1 Announce Type: new Abstract: Homelessness among US veterans remains a critical public health challenge, yet risk prediction offers a pathway for proactive intervention. In...
arXiv:2602.02735v1 Announce Type: new Abstract: Deep generative models for engineering design often require substantial computational cost, large training datasets, and extensive retraining when design requirements...
arXiv:2602.02736v1 Announce Type: new Abstract: Timely transportation of organs, patients, and medical supplies is critical to modern healthcare, particularly in emergencies and transplant scenarios where...
arXiv:2602.02738v1 Announce Type: new Abstract: The rise of music large language models (LLMs) demands robust methods of evaluating output quality, especially in distinguishing high-quality compositions...
arXiv:2602.02739v1 Announce Type: new Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geometry renders them...
arXiv:2602.02740v1 Announce Type: new Abstract: Millions of people now use non-clinical Large Language Model (LLM) tools like ChatGPT for mental well-being support. This paper investigates...
arXiv:2602.02741v1 Announce Type: new Abstract: Articulation modeling enables robots to learn joint parameters of articulated objects for effective manipulation which can then be used downstream...
arXiv:2602.02742v1 Announce Type: new Abstract: Molecular understanding is central to advancing areas such as scientific discovery, yet Large Language Models (LLMs) struggle to understand molecular...
arXiv:2602.02743v1 Announce Type: new Abstract: Cross-disciplinary teams increasingly work with high-dimensional scientific datasets, yet fragmented toolchains and limited support for shared exploration hinder collaboration. Prior...
arXiv:2602.02745v1 Announce Type: new Abstract: The ethics of human-robot interaction (HRI) have been discussed extensively based on three traditional frameworks: deontology, consequentialism, and virtue ethics....
arXiv:2602.02748v1 Announce Type: new Abstract: In this study, we investigate a robust single-machine scheduling problem under processing time uncertainty. The uncertainty is modeled using the...
arXiv:2602.02751v1 Announce Type: new Abstract: Small language models are increasingly viewed as a promising, cost-effective approach to agentic AI, with proponents claiming they are sufficiently...
arXiv:2602.02752v1 Announce Type: new Abstract: Background/Context: Large Language Models (LLMs) demonstrate strong performance on low-dimensional software engineering optimization tasks ($\le$11 features) but consistently underperform on...
arXiv:2602.02754v1 Announce Type: new Abstract: Generative artificial intelligence tools have made it easier to create realistic, synthetic non-consensual explicit imagery (popularly known as deepfake pornography;...
arXiv:2602.02760v1 Announce Type: new Abstract: Large language models are increasingly deployed as specialized agents that plan, call tools, and take actions over extended horizons. Yet...
arXiv:2602.02762v1 Announce Type: new Abstract: Semi-supervised imitation learning (SSIL) consists in learning a policy from a small dataset of action-labeled trajectories and a much larger...
arXiv:2602.02763v1 Announce Type: new Abstract: Interpretable time series deep learning systems are often assessed by checking temporal consistency on explanations, implicitly treating this as evidence...
arXiv:2602.02765v1 Announce Type: new Abstract: Vision Transformers (ViT) have been established as large-scale foundation models. However, because self-attention operates globally, they lack an explicit mechanism...
arXiv:2602.02766v1 Announce Type: new Abstract: Research on differentially private synthetic tabular data has largely focused on independent and identically distributed rows where each record corresponds...
arXiv:2602.02767v1 Announce Type: new Abstract: Continual learning (CL) aims to train models on a sequence of tasks while retaining performance on previously learned ones. A...
arXiv:2602.02768v1 Announce Type: new Abstract: The use of remote vision sensors for autonomous decision-making poses the challenge of transmitting high-volume visual data over resource-constrained channels...
arXiv:2602.02769v1 Announce Type: new Abstract: We present BiTimeCrossNet (BTCNet), a multimodal self-supervised learning framework for long physiological recordings such as overnight sleep studies. While many...
arXiv:2602.02773v1 Announce Type: new Abstract: Mobile manipulators in the home can enable people with cervical spinal cord injury (cSCI) to perform daily physical household tasks...
arXiv:2602.02774v1 Announce Type: new Abstract: With the growing emphasis on multilingual and cultural evaluation benchmarks for large language models, language and culture are often treated...