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- Scientific Events of the Lab
Scientific Events of the Lab
Upcoming Events
The Workshop on Individual Differences in Reading (IndiREAD) organized by our lab will take place at Saarland University on November 26-27, 2025. Fore more information, please, visit the workshop website.
Past Events
Runyi Yao (Oxford University, UK) gave a talk “Establishing causal relations in discourse processing” within the ERC-IDDISC project on November 25th, 2024, from 13:00 to 14:00 in building C7.2, conference room 2.11.
The talk abstract:
“Main task in discourse comprehension is determining the relationships that hold between linguistic units. Some of these relationships are referred to as coherence in formal theories of discourse—meaningful and sometimes non-obligatory connections, not governed by syntactic or semantic constraints, but instead determined pragmatically by factors including a comprehender’s world knowledge. For example, Result (cause-effect) and Explanation (effect-cause) are two such coherence relations. This talk presents results from two recent studies exploring how comprehenders establish Explanation relations during discourse processing. While previous research has shown that implicit causality (IC) verbs can bias causal inferences, recent experimental findings reveal important constraints on this phenomenon. The results demonstrate that only at-issue IC verbs effectively bias causal inferences, indicating that linguistic prominence plays a crucial role in shaping causal reasoning. Additionally, the research shows that IC expectations are sensitive to discourse structure, especially the Right Frontier Constraint. These studies contribute to our understanding of how comprehenders use linguistic and structural cues to infer Explanation relations, highlighting the interaction between lexical semantics, linguistic prominence, and discourse structure in establishing causal relations during discourse processing”.
Joshua Krause (University of Groningen, Netherlands) gave a talk “Unraveling latent cognitive progresses: A new Approach for modeling experimental effects” within the ERC-IDDISC project on November 5th, 2024, from 15:00 to 16:00 in building C7 4, conference room 1.17.
The talk abstract:
“In my talk I will present a new approach for analyzing experimental data, focused on discovering the underlying (cognitive) processes and the influence continuous or categorical experimental variables have on these. While conventional regression models (e.g., Generalized linear/additive mixed models; GLMMs & GAMMs) are a popular choice for modeling experimental data, they usually do not account explicitly for these latent processes. Hence, we can only speculate that, for example, an increase in ERP amplitude associated with decreases in word frequency might reflect more effortful lexical retrieval/identification. Instead, I propose to model the effect of experimental variables on properties of the latent (cognitive) processes underlying experimental data directly. As an example of this approach, I will present recent work (Krause et al., 2024, Journal of Cognitive Neuroscience) in which we modeled the effect of frequency on the duration of the processing stages involved in lexical decision (LD) making. I will discuss what we can learn from these models not just about LDs but about cognition in general, how we can potentially make them even better, and potential applications beyond the study of LDs.”
The Workshop on Generalized additive mixed-effects modeling taught by Joshua Krause (University of Groningen, Netherlands) within the ERC-IDDISC project took place on November 05−06, 2024 from 9:00 to 14:30 in C7.2, meeting room 2.11.
The workshop abstract:
"Linear mixed-effects models are a great way to analyze all sorts of psycho-linguistic data, but they assume the relationship between the predictor and dependent variables to be linear, which is not always the case. Generalized additive mixed models enable us to model any relationship between predictors and dependent variables, while also allowing us to take into account that these relationships might differ across participants and items. Nevertheless, their flexibility also poses challenges with interpretation, (over-)fitting and computing power. In this workshop, Joshua Krause will give us a
hands-on introduction to GAMMs, covering both theoretical and practical issues".
On April 24, 2024 Prof. Dr. Niels Taatgen (University of Groningen, Netherlands) gave a talk “Cognitive skills: the building blocks of human intelligence” in building A2.2, room 2.02 and MS Teams.
The talk abstract:
“Humans have the amazing capacity to perform new tasks with little or no instruction. To explain this remarkable ability, I propose that people, when faced with a new task, compose the necessary knowledge for that task using cognitive skills as building blocks. In our cognitive modeling research, we have shown how a small set of skills can instantiated into a variety of task models, and provide explanations for phenomena such as attentional blink and task switching costs without having to rely on assumptions about limitations of the brain. If cognitive skills are the building blocks of cognition, is important to be able to identify them, and study how they are learned. To identify cognitive skills, we use a hybrid approach, in which we use bottom-up machine learning methods to use individual differences in student performance to construct a knowledge graph, in which each node represents a combination of skills, and a possible knowledge state of the student. A first pilot study has shown the benefits of this approach in teaching arithmetic to students in the Dutch Vocational education”.
On 19.03.2024 Prof. Dr. Michael Franke (University of Tübingen) gave a talk “Cognitive & Language Sciences in the age of Large Language Models” within the ERC-IDDISC project in building A2.2, room 1.20.2 and MS Teams.
The talk abstract:
“Powerful Large Language Models, like chatGPT, produce fluent, grammatically correct, interpretable and often relevant and useful language. This raises a brutal question: What do we need linguistic theory for if all of this can be achieved without? In my talk, I will dissect the most common reaction from theorists, namely the argument that LLMs are not explanatory models in the relevant sense. I attempt to better delineate what it is that makes a model explanatory. I then proceed to resent novel work-in-progress that attempts to build explanatory, hybrid models that combine theory-driven probabilistic models of pragmatic language use and interpretation with the open-endedness of LLMs”.
The Workshop on Individual Differences in Pragmatics and Discourse (IndiPRAG) organized by our lab within the ERC-IDDISC project took place at Saarland University in Saarbrücken (Germany) on September 18−19, 2023. For more information, visit the workshop website.