AI Research

Research Solutions Unveils AI Rights Add-On to Ensure Copyright-Safe AI Use of Scientific Literature

Published

18 hours ago

September 11, 2025

Solution Enables Corporate Researchers To Safely Use Generative AI Tools With Journal Articles Through Integrated Rights Management And Publisher Partnerships

HENDERSON, Nev., Sept. 11, 2025 /PRNewswire/ — Research Solutions (NASDAQ: RSSS), a leading provider of AI-powered scientific research tools, announces the commercial launch of its AI Rights add-on for Article Galaxy, enabling corporate researchers to compliantly use generative AI tools with scientific journal content at scale. The solution addresses a critical compliance gap affecting 76% of researchers who now use AI tools in their workflows but lack clear guidance on copyright permissions for scientific content analysis.

The AI Rights add-on transforms Research Solutions’ Article Galaxy platform into a comprehensive solution for AI rights verification and acquisition, providing instant clarity on usage permissions and seamless access to acquire necessary rights. With direct partnerships with major publishers, the solution enables researchers to confidently analyze scientific literature with enterprise AI platforms like Microsoft Copilot, ChatGPT, and Claude while maintaining full copyright compliance.

“Our customers have been clear: they need AI capabilities to accelerate their research, but they cannot risk non-compliance,” said Roy W. Olivier, CEO of Research Solutions. “This launch delivers on our commitment to eliminate friction in the research workflow while creating sustainable value for publishers. We’re solving a compliance problem while enabling a new era of AI-powered scientific research.”

Research teams confront several complex obstacles when attempting to integrate AI tools into their workflows. Most publishers explicitly prohibit the use of their content in AI applications, yet no streamlined mechanism exists for acquiring necessary permissions. Research Solutions’ AI Rights add-on solves this through several key innovations:

Comprehensive Rights Management: Users can manage all AI rights sources through a single interface—whether through open access licenses, Reproduction Rights Organization agreements (RROs), direct publisher relationships, or Article Galaxy marketplace acquisition
Instant Rights Verification: Users immediately see AI usage permissions for any article, removing guesswork and compliance uncertainty
One-Click Rights Acquisition: Missing permissions can be purchased directly through the Article Galaxy interface with transparent pricing from participating publishers
Retroactive Rights Purchase: Organizations can acquire AI rights for articles previously purchased, enabling immediate compliance for existing content libraries
Organization-Wide Licensing: AI Rights acquired apply across the entire organization, eliminating per-use restrictions and ongoing compliance concerns

“The combination of generative AI and scientific literature creates unprecedented opportunities for accelerating discovery, but only when researchers can access content legally and efficiently,” said Chris Bendall, VP of Product Strategy at Research Solutions. “We’ve built a solution that makes AI analysis of scientific content both legally compliant and operationally seamless—turning what was previously a compliance risk into a competitive advantage.”

About Research Solutions

Research Solutions (NASDAQ: RSSS) is a vertical SaaS and AI company that simplifies research workflow for academic institutions, life science companies, and research organizations worldwide. As one of the only publisher-independent marketplaces for scientific, technical, and medical (STM) content, the company uniquely combines AI-powered tools—including an intelligent research assistant and full-text search capabilities—with seamless access to both open access and paywalled research. The platform enables organizations to discover, access, manage, and analyze scientific literature more efficiently, accelerating the pace of scientific discovery.

SOURCE Research Solutions, Inc. | LinkedIn | Facebook | X

For more information, visit https://www.researchsolutions.com.

SOURCE Research Solutions, Inc.

Source link

AI Research

Artificial Intelligence Cheating | Nation

Published

2 hours ago

September 12, 2025

Jae C. Hong - AP

Artificial Intelligence Cheating | Nation | hjnews.com

We recognize you are attempting to access this website from a country belonging to the European Economic Area (EEA) including the EU which
enforces the General Data Protection Regulation (GDPR) and therefore access cannot be granted at this time.

For any issues, call 435-752-2121.

Source link

AI Research

Artificial Intelligence in Healthcare Market : A Study of

Published

2 hours ago

September 12, 2025

The Editors

Global Artificial Intelligence in Healthcare Market size was valued at USD 27.07 Bn in 2024 and is expected to reach USD 347.28 Bn by 2032, at a CAGR of 37.57%

Artificial Intelligence (AI) in healthcare is reshaping the industry by enabling faster diagnosis, personalized treatment, and enhanced operational efficiency. AI-driven tools such as predictive analytics, natural language processing, and medical imaging analysis are empowering physicians with deeper insights and decision support, reducing human error and improving patient outcomes. Moreover, AI is revolutionizing drug discovery, clinical trial optimization, and remote patient monitoring, making healthcare more proactive and accessible in both developed and emerging markets.

The adoption of AI in healthcare is also being accelerated by the rising demand for telemedicine, wearable health devices, and real-time data-driven solutions. From virtual health assistants to robotic surgery, AI is driving innovation across patient care and hospital management. However, challenges such as data privacy, ethical considerations, and regulatory frameworks remain crucial in ensuring responsible deployment. As AI continues to integrate with IoT, cloud, and big data platforms, it is set to create a connected healthcare ecosystem that prioritizes precision medicine and patient-centric solutions.

Get a sample of the report https://www.maximizemarketresearch.com/request-sample/21261/

Major companies profiled in the market report include

BP Target Neutral . JPMorgan Chase & Co. . Gold Standard Carbon Clear . South Pole Group . 3Degrees . Shell. EcoAct.

Research objectives:

The latest research report has been formulated using industry-verified data. It provides a detailed understanding of the leading manufacturers and suppliers engaged in this market, their pricing analysis, product offerings, gross revenue, sales network & distribution channels, profit margins, and financial standing. The report’s insightful data is intended to enlighten the readers interested in this business sector about the lucrative growth opportunities in the Artificial Intelligence in Healthcare market.

Get access to the full description of the report @ https://www.maximizemarketresearch.com/market-report/global-artificial-intelligence-ai-healthcare-market/21261/

It has segmented the global Artificial Intelligence in Healthcare market

by Offering

Hardware

Software

Services

by Technology

Machine Learning

Natural Language Processing

Context-Aware Computing

Computer Vision

Key Objectives of the Global Artificial Intelligence in Healthcare Market Report:

The report conducts a comparative assessment of the leading market players participating in the globalArtificial Intelligence in Healthcare

The report marks the notable developments that have recently taken place in the Artificial Intelligence in Healthcare industry

It details on the strategic initiatives undertaken by the market competitors for business expansion.

It closely examines the micro- and macro-economic growth indicators, as well as the essential elements of theArtificial Intelligence in Healthcaremarket value chain.

The repot further jots down the major growth prospects for the emerging market players in the leading regions of the market

Explore More Related Report @

Engineering, Procurement, and Construction Management (EPCM) Market https://www.maximizemarketresearch.com/market-report/engineering-procurement-and-construction-management-epcm-market/73131/

Global Turbomolecular Pumps Market

https://www.maximizemarketresearch.com/market-report/global-turbomolecular-pumps-market/20730/

Contact Maximize Market Research:

3rd Floor, Navale IT Park, Phase 2

Pune Bangalore Highway, Narhe,

Pune, Maharashtra 411041, India

sales@maximizemarketresearch.com

+91 96071 95908, +91 9607365656

About Maximize Market Research:

Maximize Market Research is a multifaceted market research and consulting company with professionals from several industries. Some of the industries we cover include medical devices, pharmaceutical manufacturers, science and engineering, electronic components, industrial equipment, technology and communication, cars and automobiles, chemical products and substances, general merchandise, beverages, personal care, and automated systems. To mention a few, we provide market-verified industry estimations, technical trend analysis, crucial market research, strategic advice, competition analysis, production and demand analysis, and client impact studies

This release was published on openPR.

Source link

AI Research

Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication

Published

3 hours ago

September 12, 2025

Maysam Behmanesh, Erkan Turan, Maks Ovsjanikov

arXiv:2509.09597v1 Announce Type: cross
Abstract: Graph alignment-the problem of identifying corresponding nodes across multiple graphs-is fundamental to numerous applications. Most existing unsupervised methods embed node features into latent representations to enable cross-graph comparison without ground-truth correspondences. However, these methods suffer from two critical limitations: the degradation of node distinctiveness due to oversmoothing in GNN-based embeddings, and the misalignment of latent spaces across graphs caused by structural noise, feature heterogeneity, and training instability, ultimately leading to unreliable node correspondences. We propose a novel graph alignment framework that simultaneously enhances node distinctiveness and enforces geometric consistency across latent spaces. Our approach introduces a dual-pass encoder that combines low-pass and high-pass spectral filters to generate embeddings that are both structure-aware and highly discriminative. To address latent space misalignment, we incorporate a geometry-aware functional map module that learns bijective and isometric transformations between graph embeddings, ensuring consistent geometric relationships across different representations. Extensive experiments on graph benchmarks demonstrate that our method consistently outperforms existing unsupervised alignment baselines, exhibiting superior robustness to structural inconsistencies and challenging alignment scenarios. Additionally, comprehensive evaluation on vision-language benchmarks using diverse pretrained models shows that our framework effectively generalizes beyond graph domains, enabling unsupervised alignment of vision and language representations.

Source link