arXiv:2204. 09333v3 Announce Type: replace-cross Abstract: In recent years, with the rapid growth of Internet data, the number and types of scientific and technological resources are also rapidly expanding.
arXiv:2204. 06221v2 Announce Type: replace-cross Abstract: In the era of big data, intellectual property-oriented scientific and technological resources show the trend of large data scale, high information density, and low value density, which brings severe challenges to the effective use of intellectual property resources, and the demand for mining hidden information in intellectual property is increasing.
arXiv:2204. 04883v2 Announce Type: replace-cross Abstract: With the advent of the cloud computing era, the cost of creating, capturing, and managing information has gradually decreased.
arXiv:2204. 04887v3 Announce Type: replace-cross Abstract: Since the era of big data, the Internet has been flooded with all kinds of information.
arXiv:2204. 06142v2 Announce Type: replace-cross Abstract: Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources of experts and scholars, and these talents with great scientific and technological innovation ability are an important force to promote industrial upgrading.
arXiv:2204. 08476v2 Announce Type: replace-cross Abstract: In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased significantly.
arXiv:2607. 22684v1 Announce Type: cross Abstract: Artificial intelligence systems increasingly mediate how science is found and credited.
arXiv:2606. 28331v1 Announce Type: cross Abstract: The widespread deployment of generative artificial intelligence (AI) models has raised serious concerns about the proliferation of AI-generated content.
arXiv:2607. 21327v1 Announce Type: cross Abstract: Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics, yet suffer from temporal lag, semantic shallowness, and an inability to capture the non-linear dynamics of contemporary knowledge ecosystems.
INDRA is a research platform that integrates multiple archival collections—such as UCSF’s Industry Documents Library, Columbia and CUNY’s ToxicDocs, and Stanford’s SRITA—into a single, LLM‑readable corpus. It employs three safeguards: a closed evidentiary sandbox, real‑time provenance tagging, and a deterministic system‑level protocol to ensure that model outputs are clearly distinguished from archival evidence and from the model’s own inferences. The platform enables large‑language‑model‑powered investigations across these archives while keeping the conditions of knowledge production transparent and auditable.
arXiv:2607. 20328v1 Announce Type: cross Abstract: This study empirically analyzed generative AI as an emerging discovery pathway to academic library resources.
The article titled "10 Things I’m Learning Beyond AI to Become More Technologically Fluent" discusses the author's exploration of various technologies that are shaping the future, beyond just artificial intelligence. It is presented as part one of a series, focusing on understanding these emerging technologies and their impact.
Today we’re introducing new technology to help researchers identify content created by our tools and joining the Coalition for Content Provenance and Authenticity Steering Committee to promote industry standards.