Stay updated with the latest research and technology news
arXiv:2601.18696v1 Announce Type: new Abstract: Hardware trojan detection requires accurate identification and interpretable explanations for security engineers to validate and act on results. This work...
arXiv:2601.18697v1 Announce Type: new Abstract: LLM-based chatbots like ChatGPT have become popular tools for assisting with coding tasks. However, they often produce isolated responses and...
arXiv:2601.18698v1 Announce Type: new Abstract: Recent advances in text-to-video generation have produced visually compelling results, yet it remains unclear whether these models encode geographically equitable...
arXiv:2601.18699v1 Announce Type: new Abstract: Large language models exhibit remarkable performance across diverse tasks through pre-training and fine-tuning paradigms. However, continual fine-tuning on sequential tasks...
arXiv:2601.18700v1 Announce Type: new Abstract: Emotional Support Conversation requires not only affective expression but also grounded instrumental support to provide trustworthy guidance. However, existing ESC...
arXiv:2601.18702v1 Announce Type: new Abstract: Current paradigms in Deep Learning prioritize computational throughput over numerical precision, relying on the assumption that intelligence emerges from statistical...
arXiv:2601.18705v1 Announce Type: new Abstract: Dynamic Low Rank (DLR) methods are a promising way to reduce the computational cost and memory footprint of the high-dimensional...
arXiv:2601.18706v1 Announce Type: new Abstract: Rubrics are essential for evaluating open-ended LLM responses, especially in safety-critical domains such as healthcare. However, creating high-quality and domain-specific...
arXiv:2601.18707v1 Announce Type: new Abstract: Machine learning-based surrogate models have emerged as more efficient alternatives to numerical solvers for physical simulations over complex geometries, such...
arXiv:2601.18710v1 Announce Type: new Abstract: This paper presents a feasibility study demonstrating that quantum machine learning (QML) algorithms achieve competitive performance on real-world medical imaging...
arXiv:2601.18714v1 Announce Type: new Abstract: Localization in agricultural environments is challenging due to their unstructured nature and lack of distinctive landmarks. Although agricultural settings have...
arXiv:2601.18716v1 Announce Type: new Abstract: Alzheimer's disease (AD) is marked by the pathological accumulation of amyloid beta-42 (Abeta-42), contributing to synaptic dysfunction and neurodegeneration. While...
arXiv:2601.18721v1 Announce Type: new Abstract: A new alternative numerical procedure to the Szeg\H{o} quadrature formulas for the estimation of integrals with respect to a positive...
arXiv:2601.18722v1 Announce Type: new Abstract: When asked a question in a language less seen in its training data, current reasoning large language models (RLMs) often...
arXiv:2601.18723v1 Announce Type: new Abstract: Driven by the rapid evolution of Vision-Action and Vision-Language-Action models, imitation learning has significantly advanced robotic manipulation capabilities. However, evaluation...
arXiv:2601.18724v1 Announce Type: new Abstract: Recently, we have often observed hallucinated citations or references that do not correspond to any existing work in papers under...
arXiv:2601.18727v1 Announce Type: new Abstract: Achieving long-range, high-rate, concurrent two-way mmWave communication with power-constrained IoT devices is fundamental to scaling future ubiquitous sensing systems, yet...
arXiv:2601.18728v1 Announce Type: new Abstract: Modern generative modeling methods have demonstrated strong performance in learning complex data distributions from clean samples. In many scientific and...
arXiv:2601.18730v1 Announce Type: new Abstract: The constitutional framework of alignment aims to align large language models (LLMs) with value-laden principles written in natural language (such...
arXiv:2601.18731v1 Announce Type: new Abstract: Alignment of Large Language Models (LLMs) aims to align outputs with human preferences, and personalized alignment further adapts models to...
arXiv:2601.18734v1 Announce Type: new Abstract: Knowledge distillation improves large language model (LLM) reasoning by compressing the knowledge of a teacher LLM to train smaller LLMs....
arXiv:2601.18735v1 Announce Type: new Abstract: Vision-Language Models (VLMs) enable powerful multi-agent systems, but scaling them is economically unsustainable: coordinating heterogeneous agents under information asymmetry often...
arXiv:2601.18736v1 Announce Type: new Abstract: The rapid expansion of the Internet of Things (IoT) in domains such as smart cities, transportation, and industrial systems has...
arXiv:2601.18739v2 Announce Type: new Abstract: Out-of-distribution (OOD) detection is a fundamental requirement for the reliable deployment of artificial intelligence applications in open-world environments. However, addressing...