January 2026

arXiv:2601.08884v1 Announce Type: new Abstract: OpenACC lowers the barrier to GPU offloading, but writing high-performing pragma remains complex, requiring deep domain expertise in memory hierarchies, data movement, and parallelization strategies. Large Language Models (LLMs) present a promising potential solution for automated parallel code generation, but naive prompting often results in syntactically incorrect directives, uncompilable code, or performance that fails to exceed CPU baselines. We present a systematic prompt optimization approach to enhance OpenACC pragma generation without the prohibitive […]

Ver mais

arXiv:2601.08882v1 Announce Type: new Abstract: Deploying geospatial foundation models on resource-constrained edge devices demands compact architectures that maintain high downstream performance. However, their large parameter counts and the accuracy loss often induced by compression limit practical adoption. In this work, we leverage manifold-constrained optimization framework DLRT to compress large vision transformer-based geospatial foundation models during transfer learning. By enforcing structured low-dimensional parameterizations aligned with downstream objectives, this approach achieves strong compression while preserving task-specific accuracy. We show that […]

Ver mais

arXiv:2601.08881v1 Announce Type: new Abstract: Unified image generation and editing models suffer from severe task interference in dense diffusion transformers architectures, where a shared parameter space must compromise between conflicting objectives (e.g., local editing v.s. subject-driven generation). While the sparse Mixture-of-Experts (MoE) paradigm is a promising solution, its gating networks remain task-agnostic, operating based on local features, unaware of global task intent. This task-agnostic nature prevents meaningful specialization and fails to resolve the underlying task interference. In this […]

Ver mais

arXiv:2601.08880v1 Announce Type: new Abstract: As automated systems increasingly transition from decision support to direct execution, the problem of accountability shifts from decision quality to execution legitimacy. While optimization, execution, and feedback mechanisms are extensively modeled in contemporary AI and control architectures, the structural role of judgment remains undefined. Judgment is typically introduced as an external intervention rather than a native precondition to execution. This work does not propose a new decision-making algorithm or safety heuristic, but identifies […]

Ver mais

arXiv:2601.08879v1 Announce Type: new Abstract: This study investigates the use of computational audio analysis to examine ideological narratives in Nazi propaganda films. Employing a three-step pipeline, speaker diarization, audio transcription and psycholinguistic analysis, it reveals ideological patterns in characters. Despite current issues with speaker diarization, the methodology provides insights into character traits and propaganda narratives, suggesting scalable applications.

Ver mais

arXiv:2601.08878v1 Announce Type: new Abstract: Text-based online counselling scales across geographical and stigma barriers, yet faces practitioner shortages, lacks non-verbal cues and suffers inconsistent quality assurance. Whilst artificial intelligence offers promising solutions, its use in mental health counselling raises distinct ethical challenges. This paper analyses three AI implementation approaches – autonomous counsellor bots, AI training simulators and counsellor-facing augmentation tools. Drawing on professional codes, regulatory frameworks and scholarly literature, we identify four ethical principles – privacy, fairness, autonomy […]

Ver mais

arXiv:2601.08877v1 Announce Type: new Abstract: This paper examines refusal behavior in generative AI systems through a governance lens. Drawing on historical frameworks of censorship and contemporary design logics, it argues that refusal is not a neutral safeguard but a site of power, shaped by institutional risk management and opaque decision-making. The analysis concludes with user-centered recommendations for ethical refusal design. Keywords: Generative AI governance, AI refusal behavior, Censorship, Ethical design

Ver mais

arXiv:2601.08876v1 Announce Type: new Abstract: Semantic information in embodied AI is inherently multi-source and multi-stage, making it challenging to fully leverage for achieving stable perception-to-action loops in real-world environments. Early studies have combined manual engineering with deep neural networks, achieving notable progress in specific semantic-related embodied tasks. However, as embodied agents encounter increasingly complex environments and open-ended tasks, the demand for more generalizable and robust semantic processing capabilities has become imperative. Recent advances in foundation models (FMs) address […]

Ver mais

arXiv:2601.08875v1 Announce Type: new Abstract: Image registration under domain shift remains a fundamental challenge in computer vision and medical imaging: when source and target images exhibit systematic intensity differences, the brightness constancy assumption underlying conventional registration methods is violated, rendering correspondence estimation ill-posed. We propose SAR-Net, a unified framework that addresses this challenge through principled scene-appearance disentanglement. Our key insight is that observed images can be decomposed into domain-invariant scene representations and domain-specific appearance codes, enabling registration via […]

Ver mais

arXiv:2601.08874v1 Announce Type: new Abstract: GenAI systems are increasingly used for drafting, summarisation, and decision support, offering substantial gains in productivity and reduced cognitive load. However, the same natural language fluency that makes these systems useful can also blur the boundary between tool and companion. This boundary confusion may encourage some users to experience GenAI as empathic, benevolent, and relationally persistent. Emerging reports suggest that some users may form emotionally significant attachments to conversational agents, in some cases […]

Ver mais