相关论文: Funding the Frontier: Visualizing the Broad Impact…
Investigators, funders, and the public desire knowledge on topics and trends in publicly funded research but current efforts in manual categorization are limited in scale and understanding. We developed a semi-automated approach to extract…
Data is essential to train and fine-tune today's frontier artificial intelligence (AI) models and to develop future ones. To date, academic, legal, and regulatory work has primarily addressed how data can directly harm consumers and…
How to quantify the impact of a researcher's or an institution's body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the…
Software is an important tool for scholarly work, but software produced for research is in many cases not easily identifiable or discoverable. A potential first step in linking research and software is software identification. In this paper…
We discuss, at the macro-level of nations, the contribution of research funding and rate of international collaboration to research performance, with important implications for the science of science policy. In particular, we…
Fairness, Accountability, and Transparency (FAccT) for socio-technical systems has been a thriving area of research in recent years. An ACM conference bearing the same name has been the central venue for scholars in this area to come…
In the present academic landscape, the process of collecting data is slow, and the lax infrastructures for data collaborations lead to significant delays in coming up with and disseminating conclusive findings. Therefore, there is an…
The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context,…
There has been a large focus in recent years on making assets in scientific research findable, accessible, interoperable and reusable, collectively known as the FAIR principles. A particular area of focus lies in applying these principles…
For most problems in science and engineering we can obtain data sets that describe the observed system from various perspectives and record the behavior of its individual components. Heterogeneous data sets can be collectively mined by data…
The implementation of policies promoting the adoption of an Open Science culture must be accompanied by indicators that allow monitoring the penetration of such policies and their potential effects on research publishing and sharing…
One of the grand challenges of artificial general intelligence is developing agents capable of conducting scientific research and discovering new knowledge. While frontier models have already been used as aides to human scientists, e.g. for…
Context: With artificial intelligence (AI) being well established within the daily lives of research communities, we turn our gaze toward formal methods (FM). FM aim to provide sound and verifiable reasoning about problems in computer…
Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional…
The rapid integration of generative AI into scientific research has exposed a critical gap in academic disclosure practice. Existing frameworks for reporting AI contributions are uniformly output-oriented -- they document what AI produced,…
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in the field of medical imaging, the curation and assembling…
Measuring research impact is important for ranking publications in academic search engines and for research evaluation. Social media metrics or altmetrics measure the impact of scientific work based on social media activity. Altmetrics are…
AI policy should advance AI innovation by ensuring that its potential benefits are responsibly realized and widely shared. To achieve this, AI policymaking should place a premium on evidence: Scientific understanding and systematic analysis…
Mitigating the risks from frontier AI systems requires up-to-date and reliable information about those systems. Organizations that develop and deploy frontier systems have significant access to such information. By reporting safety-critical…
Early in researchers' careers, it is difficult to assess how good their work is or how important or influential the scholars will eventually be. Hence, funding agencies, academic departments, and others often use the Journal Impact Factor…