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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 ↗6070 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 Multimodal Knowledge Graph Completion Method for Human–Robot Collaborative Maintenance of Industrial Robots Toward Industry 5.0 ↗
Industrial robot maintenance knowledge graphs often contain missing relationships, while semantic differences among maintenance text, graph structure, and operational condition signals complicate multimodal link prediction. Sparsely connected entities further limit the available structural evidence. To address these challenges, this study proposes a prototype-enhanced multimodal knowledge contrastive learning (Pro-MKCL) framework. The framework combines modality-specific encoders, multi-head neighborhood attention, and a cross-modal Transformer to learn integrated entity representations. Ontol…
- OpenAlex · Published · First archived
LLM-Assisted Unsatisfiability Proofs for Satisfiability Modulo Theories, Oracles, and Natural Language ↗
Modern software systems routinely invoke components whose source code is unavailable, such as proprietary libraries or cloud-based APIs. Such closed-box functions provide only oracle-style access: they can be executed on concrete inputs, but their internal logic cannot be inspected. Prior work has explored augmenting SMT solvers—the foundational engines behind contemporary automated reasoning—to handle satisfiability queries over first-order formulas containing calls to such closed-box functions. However, these approaches primarily rely on testing-based techniques to search for satisfying mode…
- OpenAlex · Published · First archived
Quantum-compatible error correction using a Bayesian Dual-Gated ProbSparse transformer in discrete-variable quantum key distribution ↗
Abstract Quantum Key Distribution (QKD) enables secure key generation with information-theoretic security guaranteed by the principles of quantum mechanics. However, achieving high reconciliation efficiency, high throughput, and low frame error rates under noisy channel conditions remains a significant challenge for practical and cost-effective Discrete-Variable Quantum Key Distribution (DV-QKD) systems. To address this issue, this research proposes a Quantum-based Bayesian Dual-Gated ProbSparse Transformer (Q-BDPT) framework for quantum-compatible error correction during the reconciliation st…
- OpenAlex · Published · First archived
OptiMine: Scalable and Precise Code Optimization for Android Apps via LLM-Driven Semantic Analysis ↗
As Android applications grow in scale, latent performance issues increasingly degrade user experience and business outcomes, yet systematically identifying optimization opportunities in large codebases remains challenging. We present OptiMine, a hybrid knowledge-to-code framework that integrates large language models (LLMs) with static program analysis to automatically uncover actionable performance optimizations. OptiMine systematically transforms unstructured expert knowledge from documents, commit diffs, and reports into structured Optimization Signatures, enabling reproducible and context-…
- OpenAlex · Published · First archived
One Toolchain, Six Domains: A Multiple-Case, Document-Based Study of Rapid IoT Prototypes Built in a One-Week Immersive Course on a Master’s Program in Applied Artificial Intelligence ↗
This paper reports a document-based, multiple-case study of six Internet of Things (IoT) prototypes designed and simulated during a one-week immersive course, “IoT for Data Intelligence,” delivered in July 2026 within the professional Master in Applied Artificial Intelligence (Maestría en Inteligencia Artificial Aplicada, MNA) at Tecnológico de Monterrey. Six teams followed the same five-day toolchain IoT theory; Oracle Application Express (APEX), SQL, and REST service design; MIT App Inventor; ESP32/Wokwi simulation; and generative AI integration and produced Wokwi-simulated prototypes spanni…
- OpenAlex · Published · First archived
Monocular depth estimation for endoscopic surgery using swin transformer and conditional random fields ↗
Abstract Monocular depth estimation in endoscopic surgery is challenging due to weak tissue textures, uneven illumination, specular reflections, and frequent smoke or instrument interference. This paper proposes CRFDepth, a pseudo‑supervised framework for endoscopic monocular depth estimation. A Swin Transformer encoder extracts hierarchical global features under weak‑texture conditions. The proposed CRFDepth framework effectively addresses key challenges in endoscopic monocular depth estimation, achieving superior accuracy and robustness. A Pyramid Scene Parsing module aggregates multi‑scale…
- OpenAlex · Published · First archived
Toward a future space-based, highly scalable AI infrastructure system design ↗
The sun is the largest energy source in our solar system, and thus it warrants consideration how future AI infrastructure could most efficiently tap into that power. We explore a scalable compute system for machine learning (ML) in space: fleets of satellites equipped with solar arrays, free-space optics inter-satellite links, and Google tensor processing unit (TPU) accelerator chips. To facilitate high-bandwidth, low-latency inter-satellite communication, the satellites would be flown in close proximity. We illustrate the basic approach to formation flight via an 81-satellite cluster of 1 km…
- OpenAlex · Published · First archived
Novel encoder-only transformer-convolutional neural network hybrid model to estimate battery state-of-charge in dynamic load and temperature variation ↗
Precise state of charge (SoC) estimation is critical for optimizing lithium-ion battery performance in energy storage systems. This study proposes an innovative Lightweight Transformer using Encoder only with 1D CNN (LTEC) model to significantly improve estimation accuracy while maintaining low computational complexity. The model integrates a 1D CNN layer in place of the standard Feed-Forward Network (FFN) within the Transformer Encoder. By applying weight-shared kernels across localized time windows, the 1D CNN captures short-term dynamics and dampens high-frequency fluctuations in sensor inp…
- OpenAlex · Published · First archived
Unpacking AI Agent Participation in Issue-Centered Collaboration in Open-Source Software Development ↗
The increasing participation of AI agents in open-source software development raises questions about their role in collaborative processes. This paper investigates how AI agent participation relates to the structure and outcomes of issue-centered collaboration in open-source software projects. We adopt a process-level perspective by modeling issue handling as sequences of events and extending dynamic issue-pr entropy to distinguish between agent-related and non-agent-related contributions. Using large-scale issue event data from 83 GitHub repositories, we construct a project–month panel datase…
- OpenAlex · Published · First archived
Game Theory Research on the Development and Promotion of Artificial Intelligence Teaching Platform Based on Multi-Participant University-Enterprise Collaboration ↗
With the deep integration of artificial intelligence and education, university-enterprise cooperation has become a key approach for the development and promotion of artificial intelligence (AI) teaching platforms. However, differences in the interests of various stakeholders lead to insufficient stability in cooperation. Therefore, based on evolutionary game theory, this study constructs a dynamic game model involving enterprises, universities, and teachers. By establishing a replicating dynamic equation, the equilibrium point is solved and its stability is analyzed. Numerical simulations are…
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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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