This paper investigates the eflfects of negation in discourse comprehension. The paper is based on the finding by Mac-Donald and Just (1989) that after reading sentences such as Elizabeth bakes some bread but no cookies subjects are faster to respond to the probe bread than to the probe cookies. The question arises whether this differential availability of the relevant concepts is due to negation, or whether it reflects the fact that a bread is present in the described situation, whereas cookies are not. In order to decide between these alternatives two experiments were conducted. In Experiment 1 negated entities that are absent from the described situation were compared with non-negated entities that are present, whereas in Experiment 2 negated entities that are present in the situation were compared with non-negated entities that are absent. The results of the two experiments indicate that both factors, namely 'negation' and 'absence from situation', affect the availability of concepts during discourse processing.

This study explores whether Large Language Models (LLMs) can mimic human cognitive processes, particularly pragmatic reasoning in language processing. Focusing on how humans tend to offer semantically similar alternatives in response to negated statements, the research examines if LLMs, both base and fine-tuned, exhibit this behavior. The experiment involves a cloze task, where the models provide completions to negative sentences. Findings reveal that chat models closely resemble human behavior, while completion models align worse with human responses. This indicates that mere linguistic input statistics might be inadequate for LLMs to develop behaviours consistent with pragmatic reasoning. Instead, conversational fine-tuning appears to enable these models to adopt behaviors akin to human pragmatic reasoning. This research not only sheds light on LLMs' capabilities but also prompts further inquiry into language acquisition, especially the role of conversational interactions in developing pragmatic reasoning.

We propose a neural dynamic architecture that models negation processing. The architecture receives a visual scene and a relational phrase like ``The blue object is not to the right of the yellow object'' or ``The blue object is to the right of the green object'' as input, and autonomously determines whether the phrase correctly describes the visual scene. The model is built out of empirically founded components for perceptually grounded cognition and constrained by neural principles. We demonstrate that the model can explain two commonly found reaction time effects: the negation effect in which reaction times are higher for negated than for affirmative phrases, and the polarity-by-truth-value interaction effect in which reaction times for false negated phrases are faster than those for true negated phrases whereas the opposite is true for affirmative phrases. The model is consistent with some aspects of the two-step simulation theory.

In Experiment 1, we conducted a survey in which we asked a sample of N = 762 participants explicitly about their preferences regarding reimbursement and experimental duration of web-based experiments. Participants significantly prefer donations and raffles over other forms of reimbursement in 5-minute experiments. When experiments take 30 minutes or longer, participants significantly prefer direct payment. This finding applies to 15-minute experiments, too, if only data of PayPal account holders is analyzed (75.23% of our sample). In Experiment 2, we implicitly measured the preferences of N = 189 participants by letting them choose between experiments with different durations and forms of reimbursements. As in Experiment 1, direct payment was the preferred reimbursement in longer studies. The most popular choice of duration and reimbursement was to receive direct payment for an experiment of 60 minutes, which was selected by 57% of all participants.

Construal Level Theory (CLT) suggests that we represent objects close to us in a concrete and modal fashion, and that representations become more abstract and amodal with increasing distance from ourselves. Evidence for such an association of abstraction level and distance comes from the Implicit Association Test (IAT), where participants are faster when pressing one key for “near” and “concrete” and another key for “far” and “abstract” targets (congruent), than when “near” is paired with “abstract” and “far” with “concrete” (incongruent). However, previous experiments might have confounded distance and abstraction by employing inherently near and far targets (e.g., CHAIR vs. SUN) that might also differ in their abstractness. Here, we thus experimentally induced different distances in a learning phase before a subsequent IAT task. Even with this controlled distance manipulation, a pronounced congruency effect emerged, providing further support for an association of distance and abstraction level as suggested by CLT.