Ivan Habernal
Biographic Data
| ID | 6536549 |
|---|---|
| NAME | Ivan Habernal |
| GIVEN NAMES | Ivan |
| FAMILY NAME | Habernal |
| SIGNATURE | HABERNAL I |
| AFFILIATIONS | RU Bochum, RC-Trust. [email protected] |
| ORCID | 0000-0002-0990-4554 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
The Conundrum of Trustworthy Research on Attacking Personally Identifiable Information Removal Techniques
Removing personally identifiable information (PII) from texts is necessary to comply with various data protection regulations and to enable data sharing without compromising privacy. However, recent works show that documents sanitized by PII-removal techniques are vulnerable to reconstruction attacks. Yet, we suspect that the reported success of these attacks is largely overestimated. We critically analyze the evaluation of existing attacks and f…
Problem Solving Through Human–AI Preference-based Cooperation
While there is a widespread belief that artificial general intelligence—or even superhuman AI—is imminent, complex problems in expert domains are far from being solved. We argue that such problems require human–AI cooperation and that the current state of the art in generative AI is unable to play the role of a reliable partner due to a multitude of shortcomings, including difficulty in keeping track of a complex solution artifact (e.g., a softwa…
Argumentation Mining in User-Generated Web Discourse
The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theo…
Text, Speech and Dialogue
Argumentation Mining in User-Generated Web Discourse
The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theo…
Text, Speech and Dialogue
Argumentation Mining in User-Generated Web Discourse
The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theo…
Problem Solving Through Human–AI Preference-based Cooperation
While there is a widespread belief that artificial general intelligence—or even superhuman AI—is imminent, complex problems in expert domains are far from being solved. We argue that such problems require human–AI cooperation and that the current state of the art in generative AI is unable to play the role of a reliable partner due to a multitude of shortcomings, including difficulty in keeping track of a complex solution artifact (e.g., a softwa…
The Conundrum of Trustworthy Research on Attacking Personally Identifiable Information Removal Techniques
Removing personally identifiable information (PII) from texts is necessary to comply with various data protection regulations and to enable data sharing without compromising privacy. However, recent works show that documents sanitized by PII-removal techniques are vulnerable to reconstruction attacks. Yet, we suspect that the reported success of these attacks is largely overestimated. We critically analyze the evaluation of existing attacks and f…
Artificial Intelligence (2 works) · Computer Science (2 works) · Annotation (1 work) · Argument (complex analysis (1 work) · Argumentation theory (1 work) · Artificial intelligence (1 work) · Artificial Intelligence (incl. Robotics) (1 work) · Automatic speech recognition (1 work) · Bridge (graph theory (1 work) · Cognitive science (1 work)