63 citations · 345 across the 53 of their papers we have counts for
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Emotion-Conditioned Text Generation through Automatic Prompt Optimization
Yarik Menchaca Resendiz, Roman Klinger
Conditional natural language generation methods often require either expensive fine-tuning or training a large language model from scratch. Both are unlikely to lead to good result…
Affective Natural Language Generation of Event Descriptions through Fine-grained Appraisal Conditions
Yarik Menchaca Resendiz, Roman Klinger
Models for affective text generation have shown a remarkable progress, but they commonly rely only on basic emotion theories or valance/arousal values as conditions. This is approp…
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection
Aswathy Velutharambath, Roman Klinger
Verbal deception has been studied in psychology, forensics, and computational linguistics for a variety of reasons, like understanding behaviour patterns, identifying false testimo…
Automatic Emotion Experiencer Recognition
Maximilian Wegge, Roman Klinger
The most prominent subtask in emotion analysis is emotion classification; to assign a category to a textual unit, for instance a social media post. Many research questions from the…
An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking
Amelie Wührl, Lara Grimminger, Roman Klinger
Existing fact-checking models for biomedical claims are typically trained on synthetic or well-worded data and hardly transfer to social media content. This mismatch can be mitigat…