Early lexical development in a self-organizing neural network

By Ping Li, Igor Farkas, Brian MacWhinney. 2004

239 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

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Citations in the corpus

A Probabilistic Computational Model of Cross-Situational Word Learning (2010, unknown): “Li et al. (2004, 2007) simulate vocabulary spurt and age of acquisition eﬀects in an incremental associative model.”
Age of acquisition: its neural and computational mechanisms. (2007, unknown): “Proficiency also plays a role in semantic and lexical tasks (Chee, Hon, Lee, & Soon, 2001; Chee, Soon, Lee, & Pallier, 2004; Elston-Guettler, Paulmann, & Kotz, 2005; Mechelli et al., 2004; Meschyan & Hernandez, 2006; Xue, Dong, Jin, Zhang, & Wang, 2004).”
When and how do children develop knowledge of verb argument structure? Evidence from verb bias effects in a structural priming task (2015, methodology): “…(2002) used Contrastive Hebbian Learning to train a model to learn the relationship between referents, word forms, and syntactic information, and Li, Farkas, and MacWhinney (2004) used a self-organising Hebbian mechanism to model how we could learn the links between lexical items and semantics.”
A Multimodal Connectionist Architecture for Unsupervised Grounding of Spatial Language (2014, methodology): “For instance, the DevLex model [20] also consists of two self-organizing networks, one for lexical symbols (phonological representations) and the other for conceptual (semantic) representations, that are bidirectionally connected.”
Evolutionary optimization of growing neural gas parameters for object categorization and recognition (2010, background): “There are a number of successful applications of the GNG [6], [7], [8] but the parameter tuning for a new problem remains awkward.”
Vocabulary Growth and Reading Development across the Elementary School Years (2011, background): “Evidence is thus provided for the conceptualization of lexical development as an incremental, self-organizing neural network with phonological, orthographic and semantic knowledge continuously being extended (Li et al., 2004).”
Selective Attention and Transfer Phenomena in L2 Acquisition: Contingency, Cue Competition, Salience, Interference, Overshadowing, Blocking, and Perceptual Learning (2006, result): “Simultaneous bilingual L1 acquisition has been compared to successive L2 acquisition in recent simulations by Hernandez et al. (2005) and Li et al. (2004).”
Word learning emerges from the interaction of online referent selection and slow associative learning (2012, methodology): “…highlighting the information that is relevant to the problem (Siskind, 1996), the power of associative mechanisms (Colunga & Smith, 2005; Li et al., 2004; Mayor & Plunkett, 2010; Merriman, 1999; Regier, 2005; Samuelson, 2002), and how constraint-like behavior emerges from simpler…”
Critical periods and catastrophic interference effects in the development of self-organizing feature maps. (2008, background): “…in these cases, such simulations may employ artificial or abstract training patterns and so are not necessarily quantitative in the strictest sense (catastrophic interference effects: Ans et al., 2004; Mirman & Spivey, 2001; critical period effects: Ellis & Lambon-Ralph, 2001; Li et al., 2004).”