Papers need to be submitted during the AAAI structure. The critique course of action is going to be one-blinded, and we welcome approved and revealed papers.
Within this workshop, we want to bring jointly researchers who focus on different stages and distinct features (structured information, unstructured know-how, and awareness acquired from LMs by themselves) of your know-how lifecycle to debate the part of data while in the period of enormous language versions.
We welcome submissions from scientists engaged on related subjects such as neural system synthesis, application induction, and thought Discovering.
We will go away sufficient time for questions and solutions at the conclusion of Each individual invited converse and panel session, and We'll function a poster session to stimulate dialogue amongst authors.
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We invite the submission of authentic and higher-quality investigate papers from the subject areas connected to intersection of effective instruction and huge-scale deployment of AI methods. The subjects for SEAS 2025 contain, but aren't restricted to (you should see the workshop Web page For additional subject areas of interest):
We persuade participation from researchers in a very wide number of topics exploring AI/ML strategies to detect novel styles and anomalies inside of data and market scientific discovery. Investigate queries may perhaps include things like (but aren't restricted to): How can we automate the invention of latest scientific phenomena?
Idea of matrix and tensor factorization approaches as well as their optimization in sketching, compression and tensor completion;
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This can be a website link into the workshop Web-site. We'll polish it and populate it with all particulars Soon:
This will likely be considered a at some point workshop, such as four invited speakers, just one panel session, numerous oral displays with the accepted lengthy papers and two poster periods for all acknowledged papers which includes shorter and lengthy.
How can we embed a notion of uncertainty inside AI/ML to quantify the importance of the discovery? How do we ensure Good reproducibility of such discoveries? Which interpretable AI/ML strategies can create immediate explanations of those discoveries?
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We hope interdisciplinary collaboration to take a look at autonomous analysis check here for topics over and above current purely natural science domains. This workshop solicits viewpoints from researchers and technologies developers to look past complex challenges to better understand the desires in the human-in-the-loop scientific exploration lifecycle.