Zlata Kikteva
Biographic Data
| ID | 10724804 |
|---|---|
| NAME | Zlata Kikteva |
| GIVEN NAMES | Zlata |
| FAMILY NAME | Kikteva |
| SIGNATURE | KIKTEVA Z |
| AFFILIATIONS | University of Passau |
| ORCID | 0009-0008-7549-6182 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The dynamics of framing in dialogue
In this paper, we propose a fine-grained, empirically-driven formalisation of framing in discourse, with a particular focus on dialogical interaction. This formalisation provides an operationalization of framing that lays the foundation for subsequently (i) designing guidelines for the annotation of framing moves in large-scale dialogue datasets and (ii) implementing computational models that can be informed with the necessary cornerstones of lin…
A large-scale comparison of human-written versus ChatGPT-generated essays
ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models—both lack scientific rigor. We systematically assess the quality of AI-generated…
No prominent works on this page.
A large-scale comparison of human-written versus ChatGPT-generated essays
ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models—both lack scientific rigor. We systematically assess the quality of AI-generated…
The dynamics of framing in dialogue
In this paper, we propose a fine-grained, empirically-driven formalisation of framing in discourse, with a particular focus on dialogical interaction. This formalisation provides an operationalization of framing that lays the foundation for subsequently (i) designing guidelines for the annotation of framing moves in large-scale dialogue datasets and (ii) implementing computational models that can be informed with the necessary cornerstones of lin…
annotation guidelines (1 work) · Argumentation theory (1 work) · Argumentative (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Calculator (1 work) · Computer Science (1 work) · Data science (1 work) · Dialogue (1 work) · dialogue dataset (1 work)