Amenta, Simona, Giulia Loca, Gabriele Gianfreda, Pasquale Rinaldi & Francesco Pavani
2024.
Exploring conceptual representation and grounding through perceptual strength norms in deaf individuals.
Language and Cognition ► pp. 1 ff.
Gatti, Daniele, Marco Marelli & Luca Rinaldi
2024.
Predicting Hand Movements With Distributional Semantics: Evidence From Mouse‐Tracking.
Cognitive Science 48:1
Petilli, Marco A., Marco Marelli, Giuliana Mazzoni, Michela Marchetti, Luca Rinaldi & Daniele Gatti
2024.
From vector spaces to DRM lists: False Memory Generator, a software for automated generation of lists of stimuli inducing false memories.
Behavior Research Methods 56:4
► pp. 3779 ff.
de Varda, Andrea Gregor, Marco Marelli & Simona Amenta
2023.
Cloze probability, predictability ratings, and computational estimates for 205 English sentences, aligned with existing EEG and reading time data.
Behavior Research Methods
Gatti, Daniele, Marco Marelli, Giuliana Mazzoni, Tomaso Vecchi & Luca Rinaldi
2023.
Hands-on false memories: a combined study with distributional semantics and mouse-tracking.
Psychological Research 87:4
► pp. 1129 ff.
Gatti, Daniele, Serena Maria Stagnitto, Chiara Basile, Giuliana Mazzoni, Tomaso Vecchi, Luca Rinaldi & Serena Lecce
2023.
Individual differences in theory of mind correlate with the occurrence of false memory: A study with the DRM task.
Quarterly Journal of Experimental Psychology 76:9
► pp. 2107 ff.
Günther, Fritz, Marco Alessandro Petilli, Alessandra Vergallito & Marco Marelli
2022.
Images of the unseen: extrapolating visual representations for abstract and concrete words in a data-driven computational model.
Psychological Research 86:8
► pp. 2512 ff.
Hofmann, Markus J., Steffen Remus, Chris Biemann, Ralph Radach & Lars Kuchinke
2022.
Language Models Explain Word Reading Times Better Than Empirical Predictability.
Frontiers in Artificial Intelligence 4
Petilli, Marco A., Fritz Günther & Marco Marelli
2022.
The Flickr frequency norms: What 17 years of images tagged online tell us about lexical processing.
Behavior Research Methods 56:1
► pp. 126 ff.
Westbury, Chris & Lee H. Wurm
Wingfield, Cai & Louise Connell
2022.
Sensorimotor distance: A grounded measure of semantic similarity for 800 million concept pairs.
Behavior Research Methods 55:7
► pp. 3416 ff.
Harati, Parastoo, Chris Westbury & Milad Kiaee
2021.
Evaluating the predication model of metaphor comprehension: Using word2vec to model best/worst quality judgments of 622 novel metaphors.
Behavior Research Methods 53:5
► pp. 2214 ff.
Kumar, Abhilasha A.
2021.
Semantic memory: A review of methods, models, and current challenges.
Psychonomic Bulletin & Review 28:1
► pp. 40 ff.
Petilli, Marco A., Fritz Günther, Alessandra Vergallito, Marco Ciapparelli & Marco Marelli
2021.
Data-driven computational models reveal perceptual simulation in word processing.
Journal of Memory and Language 117
► pp. 104194 ff.
Westera, Matthijs, Abhijeet Gupta, Gemma Boleda & Sebastian Padó
2021.
Distributional Models of Category Concepts Based on Names of Category Members.
Cognitive Science 45:9
Günther, Fritz & Marco Marelli
2020.
Trying to make it work: Compositional effects in the processing of compound “nonwords”.
Quarterly Journal of Experimental Psychology 73:7
► pp. 1082 ff.
Günther, Fritz, Marco Marelli & Jens Bölte
2020.
Semantic transparency effects in German compounds: A large dataset and multiple-task investigation.
Behavior Research Methods 52:3
► pp. 1208 ff.
Günther, Fritz, Marco Alessandro Petilli & Marco Marelli
2020.
Semantic transparency is not invisibility: A computational model of perceptually-grounded conceptual combination in word processing.
Journal of Memory and Language 112
► pp. 104104 ff.
Günther, Fritz, Luca Rinaldi & Marco Marelli
2019.
Vector-Space Models of Semantic Representation From a Cognitive Perspective: A Discussion of Common Misconceptions.
Perspectives on Psychological Science 14:6
► pp. 1006 ff.
Jacobs, Arthur M.
2019.
Sentiment Analysis for Words and Fiction Characters From the Perspective of Computational (Neuro-)Poetics.
Frontiers in Robotics and AI 6
Jacobs, Arthur M. & Annette Kinder
2019.
Computing the Affective-Aesthetic Potential of Literary Texts.
AI 1:1
► pp. 11 ff.
Jacobs, Arthur M. & Annette Kinder
2022.
Computational Models of Readers' Apperceptive Mass.
Frontiers in Artificial Intelligence 5
Hofmann, Markus J., Chris Biemann, Chris Westbury, Mariam Murusidze, Markus Conrad & Arthur M. Jacobs
2018.
Simple Co‐Occurrence Statistics Reproducibly Predict Association Ratings.
Cognitive Science 42:7
► pp. 2287 ff.
Hollis, Geoff & Chris Westbury
2018.
When is best-worst best? A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms.
Behavior Research Methods 50:1
► pp. 115 ff.
This list is based on CrossRef data as of 8 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers.
Any errors therein should be reported to them.