Graph Guided Question Answer Generation for Procedural Question-Answering
In this paper, we focus on task-specific question answering (QA). To this end, we introduce a method for generating exhaustive and high-quality training data, which allows us to train compact (e.g., run on a mobile device), task-specific QA models that ...
Degutyte, Ziedune +8 more
core
How Can Generative AI Empower Domain Experts in Creating Process Models? [PDF]
Considering the human factor in information systems is a key to future digitalization efforts, as stated in the Industry5.0 research and innovation actions of the EU.
Benzin, Janik-Vasily +4 more
core +1 more source
Taxonomic structure in a set of abstract concepts. [PDF]
Persichetti AS +4 more
europepmc +1 more source
Automatic generation of creative text in Portuguese: an overview. [PDF]
Gonçalo Oliveira H.
europepmc +1 more source
Brain versus bot: Distinguishing letters of recommendation authored by humans compared with artificial intelligence. [PDF]
Preiksaitis C +5 more
europepmc +1 more source
Generative AI voting: fair collective choice is resilient to LLM biases and inconsistencies. [PDF]
Majumdar S, Elkind E, Pournaras E.
europepmc +1 more source
Investigating antiquities trafficking with generative pre-trained transformer (GPT)-3 enabled knowledge graphs: A case study. [PDF]
Graham S, Yates D, El-Roby A.
europepmc +1 more source
Language models and psychological sciences. [PDF]
Sartori G, OrrĂ¹ G.
europepmc +1 more source
TransXLT: A novel ZTD prediction method with SASR-based data reconstruction. [PDF]
Shicheng Xie +7 more
europepmc +1 more source
Medical Report Generation and Chatbot for COVID_19 Diagnosis Using Open-AI
Mehboob F +6 more
europepmc +1 more source

