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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗6043 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
A human-centred artificial intelligence and learning analytics framework for equitable personalised higher education enrolment ↗
Artificial intelligence (AI) and learning analytics are increasingly deployed within higher education to support admissions decision-making, student success initiatives, and personalised learning. However, most AI-enabled admissions systems remain narrowly focused on efficiency, prediction, and institutional optimisation, with limited attention to learner agency, educational equity, transparency, and human-centred support. This paper proposes a conceptual framework that repositions admissions as the beginning of a personalised learning journey rather than merely a selection or gatekeeping proc…
- OpenAlex · Published · First archived
Comparative analysis of 3D printing technology and conventional construction methods in construction practices: a case study based on biomimetic design and AI-generated form-finding ↗
Abstract Recently, 3D printing has emerged as a groundbreaking fabrication technology, enabling the precise fabrication of complex structures directly from digital models. Despite its potential, integrating 3D printing into architectural design and construction practices remains a significant challenge, establishing a digital construction culture worldwide. Accordingly, this paper aims to evaluate the feasibility of integrating 3D printing into practical construction applications through a comparative analysis of the production sequence of a large-scale structure fabricated using 3D printing a…
- OpenAlex · Published · First archived
EREAL: Enhancing Mathematical Reasoning through Error-Aware Learning in Large Language Models ↗
Large Language Models (LLMs) have achieved substantial progress in solving complex mathematical problems, yet they often fail to exploit the potential value embedded in their own mistakes. Existing methods either apply coarse-grained corrections or rely on costly self-reflection, overlooking valid reasoning steps and incurring high inference overhead. To address these limitations, we propose Enhancing Reasoning through Error-Aware Learning (EREAL), a framework that enables fine-grained learning from edit-localized corrections. Our approach introduces minimal-edit correction, which revises only…
- OpenAlex · Published · First archived
Machine learning driven replication free storage optimization for wearable healthcare sensors ↗
Wearable sensors (WS) are becoming an important tool for detecting and monitoring physical changes in humans, which, together with improved diagnostic techniques and clinical procedures, represents an important development in the clinical field. The information obtained from these sensors is dynamic and dependent on human activities, making efficient storage crucial for subsequent analysis. However, if data quality management is not properly handled, strategic process failures can reach up to 40%. At the same time, scalability concerns can make it difficult to scale data processing without aff…
- OpenAlex · Published · First archived
The double-edged sword effect of AI autonomy on tourists' continuance usage intention: Based on conservation of resources theory ↗
Artificial intelligence (AI) empowers tourists by improving their decision-making efficiency, while simultaneously undermining their sense of autonomy and control, thereby producing disempowering effects. The pathways and mechanisms underlying these effects require in-depth exploration. Based on conservation of resources (COR) theory, this study investigates the underlying mechanism and boundary conditions of how AI autonomy influences tourists' continuance usage intention in travel contexts. A total of 318 valid samples were collected via the Credamo platform, and a moderated mediation model…
- OpenAlex · Published · First archived
Application of machine learning for identifying plutonium diversion in molten salt reactors ↗
Molten salt reactors (MSRs) have advantages over traditional light water reactors; however, nuclear material safeguards remain an obstacle to their deployment. The nontraditional liquid fuel of the MSR designs examined in this work and additional material flow streams create challenges for safeguards. These properties not only preclude traditional item-counting safeguards but also create new material diversion pathways. The approach proposed here involves modeling a reactor similar to currently proposed molten salt reactors using Serpent and SCALE, simulating its operation under normal conditi…
- OpenAlex · Published · First archived
Enhancing IoT Security through Machine Learning: A Comprehensive Review and Future Directions ↗
The integration of machine learning (ML) into Internet of Things (IoT) systems presents transformative opportunities across various domains but also introduces numerous security challenges. This study explores the role of ML in enhancing IoT functionalities, particularly in data analytics, security, optimization, and user experience. Through a comprehensive review of literature, case studies, and expert interviews, the study highlights ML's potential to address IoT security challenges such as device heterogeneity, data privacy, network vulnerabilities, and device authentication. Moreover, the…
- Hacker News · Posted on Hacker News · First archived
New AI Research Has Me Asking: Am I Being Mean to AI? ↗
Hacker News discussion.
- GitHub · Repository created · First archived
Alpha-Park/genpark-agent-dynamic-persona-style-adapter-skill ↗
Dynamic Agent Persona & Contextual Communication Style Adapter (inspired by Personal AI Copilots). Adapts communication formality, brevity, tone, and technical depth based on channel context, user cognitive load, and sentiment feedback.
- GitHub · Repository created · First archived
alphaparkinc/genpark-agent-dynamic-persona-style-adapter-skill ↗
Dynamic Agent Persona & Contextual Communication Style Adapter (inspired by Personal AI Copilots). Adapts communication formality, brevity, tone, and technical depth based on channel context, user cognitive load, and sentiment feedback.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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