Papers by Hendrik Buschmeier
Identifying the Periodicity of Information in Natural Language (2026.acl-long)
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| Challenge: | Existing methods to detect periodicity of information in natural language are based on a canonical periodicity detection algorithm. |
| Approach: | They propose a method to detect periods in surprisal sequences in natural language . they propose to use this method to identify periods outside the distributions of typical units . |
| Outcome: | The proposed method can detect significant periods in a single document. |
Are Multimodal Large Language Models Pragmatically Competent Listeners in Simple Reference Resolution Tasks? (2025.findings-acl)
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| Challenge: | Existing models are unable to resolve references to abstract visual stimuli, such as color patches and color grids, but their pragmatic capabilities are still a challenge for state-of-the-art MLLMs. |
| Approach: | They investigate whether multimodal large language models are able to resolve references to abstract visual stimuli, such as color patches and color grids, in a well-known reference resolution paradigm. |
| Outcome: | The proposed model can resolve references to abstract visual stimuli in dyadic reference games. |
Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study (2023.findings-emnlp)
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| Challenge: | Existing studies have shown that nonverbal behaviours are rich in communicative functions, such as gaze, head movements, and speech-accompanying manual gestures. |
| Approach: | They train a transformer-based neural sequence model to process gaze data extracted from video-recorded conversations and compute its information density. |
| Outcome: | The proposed model computes listeners’ gaze behaviour and the information density of speech using a pre-trained language model. |
How Much Does Nonverbal Communication Conform to Entropy Rate Constancy?: A Case Study on Listener Gaze in Interaction (2024.findings-acl)
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| Challenge: | Whether the Entropy Rate Constancy principle applies to nonverbal communication signals is still under investigation. |
| Approach: | They perform empirical analyses of video-recorded dialogue data and investigate whether listener gaze adheres to the Entropy Rate Constancy principle. |
| Outcome: | The results show that the ERC principle holds for listener gaze, and that linguistic factors syntactic complexity and turn transition potential are weakly correlated with local entropy of listener gaze. |
Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models (2026.acl-long)
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| Challenge: | Backchannels and fillers are important linguistic expressions in dialogue, but often ignored in modern transformer-based language models. |
| Approach: | They use clustering analysis to learn backchannels and fillers in dialogues in English and Japanese and use natural language generation metrics to confirm this. |
| Outcome: | The proposed models can learn representations of backchannels and fillers using three fine-tuning strategies. |
The Illusion of Competence: Evaluating the Effect of Explanations on Users’ Mental Models of Visual Question Answering Systems (2024.emnlp-main)
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Judith Sieker, Simeon Junker, Ronja Utescher, Nazia Attari, Heiko Wersing, Hendrik Buschmeier, Sina Zarrieß
| Challenge: | Using visual inputs, we hypothesize that explanations will make limited AI capabilities more transparent to users, but our results show that explanation increases users’ perceptions of the system’s competence regardless of its actual performance. |
| Approach: | They employ a visual question answer and explanation task where participants control the AI system’s limitations by manipulating visual inputs. |
| Outcome: | The proposed explanations do not increase users’ perceptions of the system’s competence regardless of its actual performance. |