Search · four archives
Search · four archives
21 papers · ranked by Valyu relevance
Yingji Zhang
| | | | Basic Concepts, Terms, and Abbreviations | 18 | |---|-------------|------------------|-----------------------------------------------------|----| | | Abstract | | | 21 | | | Declaration | | | 22 | | | | Acknowledgements | | 23 | | 1 | | Introduction | | 24 | | | 1.1 | Motivation . | | 24 | | | | 1.1.1 |…
Xiaochen Y. Zheng, Mona M. Garvert, Hanneke E. M. den Ouden, Lisa I. Horstman + 2 more
The ability to generalize previously learned knowledge to novel situations is crucial for adaptive behavior, representing a form of cognitive flexibility that is particularly relevant in language. Humans excel at combining linguistic building blocks to infer the meanings of novel compositional words, such as…
Martin Ulrich, Marcel Harpaintner, Natalie M. Trumpp, Alexander Berger + 2 more
Grounded cognition theories propose that interactions with situations establish experiential memory traces that constitute conceptual meaning. However, as abstract scientific concepts are frequently learned through language, a proposed indirect grounding mechanism postulates that modal representations are extrapolated…
Kiran Pala, S. Shalu, Vasudevan Nedumpozhimana, Kamal Kumar Choudhary
We introduce a geometric semantic model designed to capture fine-grained semantic representations in a multidimensional space. Building on this model, we develop a novel annotation framework that facilitates detailed semantic analysis across languages. Central to our approach is a set of Parts-of-Sense Inference (POSI)…
Hamoud Alhazmi, Jiachen Jiang
Understanding abstract meanings is crucial for advanced language comprehension. Despite extensive research, abstract words remain challenging due to their non-concrete, high-level semantics. SemEval-2021 Task 4 (ReCAM) evaluates models' ability to interpret abstract concepts by presenting passages with questions and…
Yejin Cho, Katrin Erk
Coffee and tea share many properties, yet they evoke strikingly different situations, atmospheres, and affective associations. These situated dimensions of word meaning are real and systematic, but they remain implicit in most computational representations of lexical meaning. We propose Scene Abstraction, a framework…
Marianna Bolognesi
The concreteness effect has long been associated with embodied theories of language, which propose that concrete words are easier to process than abstract ones because they more directly engage perceptual and motor simulations. However, empirical findings on this effect remain mixed. This paper argues that such…
Zhiwei Cai, Lixia Wang, Jingchen Bu, Ning Fan
Embodied cognition theory posits that semantic representations are instantiated through two primary mechanisms: perceptual-motor simulation and conceptual metaphor. To examine how lexical concreteness influences the embodied representation in learners of Chinese as a second language, two experiments were conducted. In…
Rocco Chiou, Francesca M. Branzi, Elizabeth Jefferies
Despite its well-established role in memory-guided cognition, whether and how the angular gyrus (AG) contributes to semantic processing remains unresolved. Connectomic work links the AG to abstract mentation, yet neuroimaging studies paradoxically show greater AG engagement for concrete than abstract semantics. To…
Daria Goriachun, Jonathan Mirault, Johannes C. Ziegler, Kristof Strijkers
Social interaction is argued to play a crucial role for grounding abstract knowledge, yet empirical evidence is scarce. To investigate whether social interaction affects the processing of abstract words, 60 French speakers semantically categorized the degree of socialness and concreteness of words either individually…
Daniel L. Kimmel, Kimberly L. Stachenfeld, Nikolaus Kriegeskorte, Stefano Fusi + 2 more
Abstraction and generalization are essential for flexible decision-making in novel situations. Recent work in humans and monkeys has shown how abstract variables are encoded by the representational geometry of neural population activity. However, these observations—which are typically made after learning has…
Armin Hakkak Moghadam Torbati, Narges Davoudi
representations allow the brain to extract shared structure across different experiences and generalize knowledge beyond individual situations. Although previous studies have shown that representational geometry plays a critical role in supporting abstraction, it remains unclear how the composition of neuronal…
Alexander Modell
This paper introduces the Manifold Probe, a supervised method for discovering representation manifolds in superposition. The method generalizes linear regression probes by learning the space of features of a concept that can be linearly predicted from the representations, and then learning the directions used to encode…
Yildiz Culcu
Machine learning models increasingly function as representational systems, yet the philosophical assumptions underlying their internal structures remain largely unexamined. This paper develops a structuralist decision framework for classifying the implicit ontological commitments made in machine learning research on…
Katarzyna Jurewicz, Yohaï-Eliel Berreby, B. Suresh Krishna
Visual attention is shaped both by low-level perceptual features and by the semantic properties of scene regions. However, compared to the salience of low-level image features, the characterization of image properties that lead to scene understanding has been more difficult. The semantic properties of scene regions…
Melissa Franch, Kalman A. Katlowitz, Elizabeth A. Mickiewicz, James L. Belanger + 12 more
Some accounts of the etiology of autism emphasize core impairments in predictive coding, or, more fundamentally, integration of contextual information into perceptual processes. This idea has the potential to link symptoms of autism to specific neurocomputational processes, and is especially promising for…
Authors not listed
Machine learning is increasingly used to predict reaction properties such as barrier heights, reaction energies, rates, or yields, as well as the underlying molecular geometries, including transition state structures. While such predictions have the potential to provide mechanistic insight for high-impact applications…
Orhan Soyuhos, Taylor R. Hayes, Wenqing Hu, Taylor P. Hamel + 3 more
In humans and other primates, high-acuity vision is restricted to the fovea, requiring frequent saccadic eye movements to sample visual information, a process known as overt attention. Classical visual salience theory explains how low-level image features guide these movements, but recent human studies have shown that…
Authors not listed
RNA molecules fold into complex three-dimensional structures that determine their function. A wide range of mathematical frameworks, such as chord diagrams, fatgraphs, and context-free grammars, have been used to represent these structures; however, these models have largely been developed from mathematical motivations…
Jingyue Zhang, J. D. Zamfirescu-Pereira, Elena L. Glassman, Damien Masson + 1 more
Traditional human-computer interaction takes place through formallyspecified systems like structured UIs and programming languages. Recent AI systems promise a new set of informal interactions with computers through natural language and other notational forms. These informal interactions can then lead to formal…
Authors not listed
Computational methods for predictive modeling have been increasingly utilized in the early stages of drug discovery to supplement high-throughput screening. The advent of highly efficient and complex machine learning architectures necessitates new methods of collating the plethora of topological, geometrical, and…