11 citations · 18 across the 12 of their papers we have counts for
10 papers · 1 filter
Predicting States of Understanding in Explanatory Interactions Using Cognitive Load-Related Linguistic Cues
Yu Wang, Olcay Türk, Angela Grimminger +1
We investigate how verbal and nonverbal linguistic features, exhibited by speakers and listeners in dialogue, can contribute to predicting the listener's state of understanding in…
Reference Games as a Testbed for the Alignment of Model Uncertainty and Clarification Requests
Manar Ali, Judith Sieker, Sina Zarrieß +1
In human conversation, both interlocutors play an active role in maintaining mutual understanding. When listeners are uncertain about what speakers mean, for example, they can requ…
Dialogue Is Not Enough to Make a Communicative BabyLM (But Neither Is Developmentally Inspired Reinforcement Learning)
Francesca Padovani, Bastian Bunzeck, Manar Ali +4
We investigate whether pre-training exclusively on dialogue data results in formally and functionally apt small language models. Based on this pre-trained llamalogue model, we empl…
Identifying the Periodicity of Information in Natural Language
Yulin Ou, Yu Wang, Yang Xu +1
Recent theoretical advancement of information density in natural language has brought the following question on desk: To what degree does natural language exhibit periodicity patte…
Conversational Implicatures: Modelling Relevance Theory Probabilistically
Christoph Unger, Hendrik Buschmeier
Recent advances in Bayesian probability theory and its application to cognitive science in combination with the development of a new generation of computational tools and methods f…
Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models
Yu Wang, Leyi Lao, Langchu Huang +3
Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based language models (LMs). Here, we s…
Are Multimodal Large Language Models Pragmatically Competent Listeners in Simple Reference Resolution Tasks?
Simeon Junker, Manar Ali, Larissa Koch +2
We investigate the linguistic abilities of multimodal large language models in reference resolution tasks featuring simple yet abstract visual stimuli, such as color patches and co…
Revisiting the Phenomenon of Syntactic Complexity Convergence on German Dialogue Data
Yu Wang, Hendrik Buschmeier
We revisit the phenomenon of syntactic complexity convergence in conversational interaction, originally found for English dialogue, which has theoretical implication for dialogical…
The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering Systems
Judith Sieker, Simeon Junker, Ronja Utescher +4
We examine how users perceive the limitations of an AI system when it encounters a task that it cannot perform perfectly and whether providing explanations alongside its answers ai…
Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative Analysis
Ildikó Pilán, Laurent Prévot, Hendrik Buschmeier +1
Scripted dialogues such as movie and TV subtitles constitute a widespread source of training data for conversational NLP models. However, there are notable linguistic differences b…