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arXiv:2601.17344v1 Announce Type: new Abstract: Large language model (LLM) agents with extended autonomy unlock new capabilities, but also introduce heightened challenges for LLM safety. In...
arXiv:2601.17346v1 Announce Type: new Abstract: The integration of large language models (LLMs) into intelligent tutoring systems offers transformative potential for personalized learning in higher education....
arXiv:2601.17348v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in socially sensitive applications, yet their behavior with respect to disability remains underexplored. We...
arXiv:2601.17349v1 Announce Type: new Abstract: In the current era of mobile internet, Lightweight Low-Light Image Enhancement (L3IE) is critical for mobile devices, which faces a...
arXiv:2601.17350v1 Announce Type: new Abstract: Neural Radiance Fields (NeRF) have demonstrated remarkable performance in novel view synthesis. However, there is much improvement room on restoring...
arXiv:2601.17351v1 Announce Type: new Abstract: For a growing number of people, AI chatbots have become close personal companions. Despite rising scholarly attention, theoretical accounts of...
arXiv:2601.17352v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) has emerged as a powerful remote sensing tool for mineral exploration, capitalizing on unique spectral signatures of...
arXiv:2601.17354v1 Announce Type: new Abstract: Efficient and high-fidelity 3D scene modeling is a long-standing pursuit in computer graphics. While recent 3D Gaussian Splatting (3DGS) methods...
arXiv:2601.17355v1 Announce Type: new Abstract: Improvements in software defined networking allow for policy to be informed and modified by data-driven applications that can adjust policy...
arXiv:2601.17356v1 Announce Type: new Abstract: Obfuscation substantially increases the interpretation cost of smart-contract auditing, while the comparability and transferability of obfuscation signals across chains remain...
arXiv:2601.17357v1 Announce Type: new Abstract: Large language models and deep neural networks achieve strong performance but suffer from reliability issues and high computational cost. This...
arXiv:2601.17359v1 Announce Type: new Abstract: The traditional use-case of query performance prediction (QPP) is to identify which queries perform well and which perform poorly for...
arXiv:2601.17360v1 Announce Type: new Abstract: Machine learning systems can produce personalized outputs that allow an adversary to infer sensitive input attributes at inference time. We...
arXiv:2601.17363v1 Announce Type: new Abstract: This study investigates whether readers prefer AI-generated short stories in Italian over one written by a renowned Italian author. In...
arXiv:2601.17364v1 Announce Type: new Abstract: This study uses Jordanian law as a case study to explore the fine-tuning of the Llama-3.1 large language model for...
arXiv:2601.17365v1 Announce Type: new Abstract: This paper aims to investigate the dynamic response of a material body undergoing fracture subjected to high strain rate loading...
arXiv:2601.17366v1 Announce Type: new Abstract: Existing displacement strategies in semi-supervised segmentation only operate on rectangular regions, ignoring anatomical structures and resulting in boundary distortions and...
arXiv:2601.17367v1 Announce Type: new Abstract: The quadratic complexity of standard attention mechanisms poses a significant scalability bottleneck for large language models (LLMs) in long-context scenarios....
arXiv:2601.17368v1 Announce Type: new Abstract: Privacy Policies are a cornerstone of informed consent, yet a persistent gap exists between their legal intent and practical efficacy....
arXiv:2601.17371v1 Announce Type: new Abstract: Identifying deepfake videos on social media platforms is challenged by dynamic spatio-temporal artifacts and inadequate user tools. This hinders both...
arXiv:2601.17373v1 Announce Type: new Abstract: As Smart Home Personal Assistants (SPAs) evolve into social agents, understanding user privacy necessitates interpersonal communication frameworks, such as Privacy...
arXiv:2601.17375v1 Announce Type: new Abstract: In this paper, we develop a class of samplers for the diffusion model using the operator-splitting technique. The linear drift...
arXiv:2601.17376v1 Announce Type: new Abstract: The advancement of Time Series Foundation Models (TSFMs) has been driven primarily by large-scale pre-training, but inference-time compute potential remains...
arXiv:2601.17377v1 Announce Type: new Abstract: The scientific peer-review process is facing a shortage of human resources due to the rapid growth in the number of...