Linguistic representations are taken by some to be representations of something, specifically of Standard Linguistic Entities, such as phonemes, clauses, noun phrases etc. This perspective takes them to be intentional. Rey (2021) further argues that the SLEs themselves are inexistent. Here I argue that linguistic representations are simply structures, abstractions of brain states, and hence not intentional, and show how they nevertheless connect to the systems that use them.

This book is nominally about linguistic representation. But, since it is we who do the representing, it is also about us. And, since it is the universe which we represent, it is also about the universe. In the end, then, this book is about everything, which, since it is a philosophy book, is as it should be. I recognize that it is nowadays unfashionable to write books about every thing. Philosophers of language, it will be said, ought to stick (...) to writing about language; philosophers of science, to writing about science; epis temologists, to writing about knowing; and so on. The real world, however, perversely refuses to carve itself up so neatly, and, although I recognize that the real w,orld is nowadays also unfashionable, in the end I judged that one might get closer to the truth of various matters by going along with it. So I have done so. lt was Wilfrid Sellars who initially convinced me of the virtues of this way of proceeding. At this point one normally says something like "The debt that this book owes him is immense". I would say it too, were it not to understate the case, From Wilfrid, I learned to think about things. If the upshot of my thinking tends, as it obviously does, to show a general con silience with the upshot of his, it is primarily because he is so very good at it - and he had a head start. (shrink)

Resumen En el texto se expone un proceso de modelación basado en dos consideraciones (Sec. 2): que los modelos son autónomos y que sus metas directas son al menos tres: estar bien construidos, adecuarse al mundo empírico y ser capaces de realizar tareas subrogatorias. Para ello, se esbozan varios ingredientes fundamentales de la tarea modeladora en la lingüística basada en evidencias, así como los de un marco formal elegido para representar aquellos. La tercera sección está dedicada a aplicar el presente (...) análisis al caso de las redes complejas con el fin de que conceptos clave como la validez, la fiabilidad y la replicabilidad de la modelación, así como el concepto de diseño experimental en RC, se puedan observar desde un prisma representacional. La sección cuarta refleja las capacidades aplicativas de (RC), especialmente en el caso del aprendizaje del lenguaje en casos atípicos y a menudo socialmente marginados. A modo de cierre, la conclusión resume la puesta en práctica de la herramienta RC. Abstract A modeling process is initially outlined based on two considerations (Sec. 2), namely that models themselves are autonomous and that their direct goals are at least threefold: to be well constructed, to fit the empirical world, and to be able to perform subrogative tasks. This section outlines the fundamental elements of the modeling task in evidence-based linguistics, as well as those of a formal framework chosen to represent the former. The third section is devoted to applying the present theoretical analysis to the case of complex networks (CN), so that key concepts such as validity, reliability and replicability of modeling, as well as the concept of experimental design in complex networks, can be viewed from a representational perspective. The fourth section reflects the application capabilities of CN, especially in the case of language learning in atypical and often socially marginalized cases. Finally, the conclusion summarizes the implementation of the CN-tool. (shrink)

Within the cognitive sciences, most researchers assume that it is the job of linguists to investigate how language is represented, and that they do so largely by building theories based on explicit judgments about patterns of acceptability – whereas it is the task of psychologists to determine how language is processed, and that in doing so, they do not typically question the linguists' representational assumptions. We challenge this division of labor by arguing that structural priming provides an implicit method of (...) investigating linguistic representations that should end the current reliance on acceptability judgments. Moreover, structural priming has now reached sufficient methodological maturity to provide substantial evidence about such representations. We argue that evidence from speakers' tendency to repeat their own and others' structural choices supports a linguistic architecture involving a single shallow level of syntax connected to a semantic level containing information about quantification, thematic relations, and information structure, as well as to a phonological level. Many of the linguistic distinctions often used to support complex syntactic structure are instead captured by semantics; however, the syntactic level includes some specification of “missing” elements that are not realized at the phonological level. We also show that structural priming provides evidence about the consistency of representations across languages and about language development. In sum, we propose that structural priming provides a new basis for understanding the nature of language. (shrink)

An essential ingredient of language use is our ability to reason about utterances as intentional actions. Linguistic representations are the natural substrate for such reasoning, and models from computational semantics can often be seen as providing an infrastructure to carry out such inferences from rich and accurate grammatical descriptions. Exploring such inferences offers a productive pragmatic perspective on problems of interpretation, and promises to leverage semantic representations in more flexible and more general tools that compute with meaning.

Recent scholarship emphasizes the scaffolding role of language for cognition. Language, it is claimed, is a cognition-enhancing niche (Clark, 2006), a programming tool for cognition (Lupyan and Bergen, 2016), even a neuroenhancement (Dove, 2019), and augments cognitive functions such as memory, categorization, cognitive control as well as meta-cognitive abilities (‘thinking about thinking’). Yet the notion that language enhances or augments cognition does not fit in with embodied approaches to language processing, or so we will argue. Accounts aiming to explain how (...) language enhances various cognitive functions often employ a notion of abstract representation. Yet embodied approaches to language processing have it that language processing crucially, according to some accounts even exclusively, involves embodied, modality-specific, i.e. non-abstract representations. In coming to understand a particular phrase or sentence, a prior experience has to be simulated or reenacted. The representation thus activated is embodied (modality-specific) as sensorimotor regions of the brain are thereby recruited. In the paper, we will first discuss the notion of representation, clarify what it takes for a representation to be embodied or abstract respectively, and distinguish between conceptual and (other) linguistic representations. We will then put forward a characterization of cognitive control and examine its representational infrastructure. The remainder of the paper will be devoted to arguing that language augments cognitive control. To that end, we will draw on two lines of research, which investigate how language augments cognitive control: i. research on the availability of linguistic labels, and ii. research on the active usage of a linguistic code, specifically in inner speech. Eventually, we will argue that the cognition-enhancing capacity of language can be explained once we assume that it provides us with a. abstract, non-embodied representations, and with b. abstract, sparse linguistic representations that may serve as easy-to-manipulate placeholders for fully embodied or otherwise more detailed representations. (shrink)

Papers presented at a seminar held in 2011 organized by the Department of Philosophy, University of Hyderabad.

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application (...) of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks. (shrink)

This paper presents a computational model that integrates a dynamically structured holographic memory system into the ACT-R cognitive architecture to explain how linguistic representations are encoded and accessed in memory. ACT-R currently serves as the most precise expression of the moment-by-moment working memory retrievals that support sentence comprehension. The ACT-R model of sentence comprehension is able to capture a range of linguistic phenomena, but there are cases where the model makes the wrong predictions, such as the over-prediction (...) of retrieval interference effects during sentence comprehension. Here, we investigate one such case involving the processing of sentences with negative polarity items and consider how a dynamically structured holographic memory system might provide a cognitively plausible and principled explanation of some previously unexplained effects. Specifically, we show that by replacing ACT-R's declarative memory with a dynamically structured memory, we can explain a wider range of behavioral data involving reading times and judgments of grammaticality. We show that our integrated model provides a better fit to human error rates and response latencies than the original ACT-R model. These results provide proof-of-concept for the unification of two independent computational cognitive frameworks. (shrink)

This paper presents a computational model that integrates a dynamically structured holographic memory system into the ACT-R cognitive architecture to explain how linguistic representations are encoded and accessed in memory. ACT-R currently serves as the most precise expression of the moment-by-moment working memory retrievals that support sentence comprehension. The ACT-R model of sentence comprehension is able to capture a range of linguistic phenomena, but there are cases where the model makes the wrong predictions, such as the over-prediction (...) of retrieval interference effects during sentence comprehension. Here, we investigate one such case involving the processing of sentences with negative polarity items and consider how a dynamically structured holographic memory system might provide a cognitively plausible and principled explanation of some previously unexplained effects. Specifically, we show that by replacing ACT-R's declarative memory with a dynamically structured memory, we can explain a wider range of behavioral data involving reading times and judgments of grammaticality. We show that our integrated model provides a better fit to human error rates and response latencies than the original ACT-R model. These results provide proof-of-concept for the unification of two independent computational cognitive frameworks. (shrink)

We investigate the hypothesis that our conceptual systems provide two formally distinct ways of representing categories by investigating the manner in which lexical nominals (e.g., tree, picnic table) and phrasal nominals (e.g., black bird, birds that like rice) are interpreted. Four experiments found that lexical nominals may be mapped onto kind representations, whereas phrasal nominals map onto class representations but not kind representations. Experiment 1 found that phrasal nominals, unlike lexical nominals, are mapped onto categories whose members (...) need not be of a single kind. Experiments 2 and 3 found that categories named by lexical nominals enter into both class inclusion and kind hierarchies and thus support both class inclusion (is a) and kind specification (kind of) relations, whereas phrasal nominals map onto class representations which support only class inclusion relations. Experiment 4 showed that the two types of nominals represent hierarchical relations in different ways. Phrasal nominals (e.g., white bear) are mapped onto classes that have criteria of membership in addition to those specified by the class picked out by the head noun of the phrase (e.g., bear). In contrast, lexical nominals (e.g., polar bear) specify one way to meet the criteria specified by the more general kind concept (e.g., bear). Implications for the language–conceptual system interface, representation of hierarchical relations, lexicalization, and theories of conceptual combination are discussed. (shrink)

José L. Zalabardo defends a pragmatist account of what grounds the meaning of central semantic discourses--ascriptions of truth, of propositional attitudes, and of meanings. He argues that it is the procedures that regulate acceptance and rejection that give the sentences of these discourses their meanings, and explores the application of the pragmatist template to ethical discourse. The pragmatist approach is presented as an alternative to representationalist accounts of the meaning grounds of declarative sentences, according to which a sentence has the (...) meaning it has as a result of links with the bits of the world that it purports to represent. Zalabardo develops a version of the open-question argument to support the claim that the meaning grounds of the discourses he focuses on cannot receive representationalist accounts. It is generally assumed that a declarative sentence cannot perform the function of representing the world unless it has a representationalist meaning ground. Zalabardo rejects this assumption, arguing that sentences with pragmatist meaning grounds can represent the world in exactly the same sense that sentences with representationalist meaning grounds do. This requires that there are states of affairs that the target sentences represent as obtaining, and Zalabardo develops an account of the nature of the states of affairs that can play this role for sentences with pragmatist meaning grounds. Pragmatist Semantics concludes by developing the suggestion that the meaning grounds of all our representational discourses might be ultimately pragmatist. (shrink)

Structural priming is a useful tool for investigating linguistics representations. We argue that structural priming can be extended to the investigation of pragmatic representations such as Gricean enrichments. That is not to say priming is without its limitations, however. Interpreting a failure to observe priming may not be as simple as Branigan & Pickering imply.

This article will provide a unifying perspective on perception and cognition via the route of linguistic representations of emotion. Linguistic representations of emotions provide a fertile ground for explorations into the nature and form of integration of perception and cognition because emotion has facets of both perceptual and cognitive processes. In particular, this article shows that certain types of linguistic representations of emotion allow for the integration of perception and cognition through a series of (...) steps and operations in cognitive systems, whereas certain other linguistic representations of emotion are not so representationally structured as to permit the unity of perception and cognition. It turns out that the types of linguistic representations of emotion that readily permit the desired unity of perception and cognition are exactly those that are linguistically encoded emotive representations of everyday objects, events, and things around us. It is these ordinary objects, events and things that provide the scaffolding for task-dependent or goal-oriented activities of cognitive systems including autonomous systems. In this way, cognitive systems can be saliently tuned to the outer world by being motivated and also subtly governed by emotion-driven representations. This helps not only tie together perceptual and cognitive processes via the interface between language and emotive representations, but also reveal the limits of emotive representations in amalgamating perceptual and cognitive processes in cognitive systems. (shrink)

The explosion of data grows at a rate of roughly five trillion bits a second, giving rise to greater urgency in conceptualizing the infosphere and understanding its implications for knowledge and public policy. Philosophers of technology and information technologists alike who wrestle with ontological and epistemological questions of digital information tend to emphasize, as Floridi does, information as our new ecosystem and human beings as interconnected informational organisms, inforgs at home in ambient intelligence. But the linguistic and conceptual (...) class='Hi'>representations of Big Data—the massive volume of both structured and unstructured data—and the real world practice of data-mining for patterns and meaningful interpretation of evidence reveal tension and ambiguity in the bold promise of data analytics. This paper explores the tacit epistemology of the rhetoric and representation of Big Data and suggests a richer account of its ambiguities and the paradox of its real world materiality. We argue that Big Data should be recognized as manifesting multiple and conflicting trajectories that reflect human intentionality and particular patterns of power and authority. Such patterns require attentive exploration and moral appraisal if we are to resist simplistic informationist ontologies of Big Data, and the subtle forms of control in the political ecology of Big Data that undermine its promise as transformational knowledge. (shrink)

Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling (...) linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling. (shrink)

Georges Rey presents a much-needed philosophical defense of Noam Chomsky's famous view of human language, as an internal, innate computational system. But he also offers a critical examination of problematic developments of this view, to do with innateness, ontology, intentionality, and other issues of interdisciplinary interest.

Linguistic Issues in Language Technology (LiLT) is an open-access journal that focuses on the relationships between linguistic insights and language technology. In conjunction with machine learning and statistical techniques, deeper and more sophisticated models of language and speech are needed to make significant progress in both existing and newly emerging areas of computational language analysis. The vast quantity of electronically accessible natural language data (text and speech, annotated and unannotated, formal and informal) provides unprecedented opportunities for data-intensive analysis (...) of linguistic phenomena, which can in turn enrich computational methods. Taking an eclectic view on methodology, LiLT provides a forum for this work. In this volume, contributors offer new perspectives on semantic representations for textual inference. (shrink)

The nature of linguistic understanding is a much-debated topic. Among the issues that have been discussed, two questions have recently received a lot of attention: (Q1) ‘Are states of understanding direct (i.e. represent solely what is said) or indirect (i.e. represent what is said as being said/asserted)?’ and (Q2) ‘What kind of mental attitude is linguistic understanding (e.g. knowledge, belief, seeming)?’ This paper argues that, contrary to what is commonly assumed, there is no straightforward answer to either of (...) these questions. This is because linguistic understanding cannot be identified with a single mental attitude towards a particular representation. Instead, we should characterize states of linguistic understanding as involving complex representational structures generated by a dual-stream process. The first stream operates on direct representations of what is said, while the second operates on representations of what is said as being said/asserted by a given source. Both these streams feed a situation model, i.e. a complex representation of a state of affairs described by a given piece of discourse. (shrink)

Distributed Cognition and Integrational Linguistics have much in common. Both approaches see communicative activity and intelligent behaviour in general as strongly con- text-dependent and action-oriented, and brains as permeated by history. But there is some ten- sion between the two frameworks on three important issues. The majority of theorists of distributed cognition want to maintain some notions of mental representation and computa- tion, and to seek generalizations and patterns in the various ways in which creatures like us couple with technologies, (...) media, and other agents; many also want to offer explanations at subpersonal levels which may undercut the autonomy of personal-level accounts. In contrast, dominant views in integrational linguistics reject all invocation of representation, resist the explanatory search for similarity across contexts and moments, and see linguistics as a lay dis- cipline which should not offer explanations in terms alien to ordinary agents. On each of these issues, I argue that integrationists could move closer to the distributed cognition frame- work without losing the most important aspects of their view: integrationist criticisms of mainstream or classical theories can be respected while alliances with revised cognitivist views about representation, context, and explanation are developed. Ó 2004 Elsevier Ltd. All rights reserved. (shrink)

Embedded and embodied approaches to cognition urge that (1) complicated internal representations may be avoided by letting features of the environment drive behavior, and (2) environmental structures can play an enabling role in cognition, allowing prior cognitive processes to solve novel tasks. Such approaches are thus in a natural position to oppose the ‘thesis of linguistic structuring’: The claim that the ability to use language results in a wholesale recapitulation of linguistic structure in onboard mental representation. Prominent (...) examples of researchers adopting this critical stance include Andy Clark, Michael Wheeler, and Mark Rowlands. But is such opposition warranted? Since each of these authors advocate accounts of mental representation that are broadly connectionist, I survey research on formal language computation in artificial neural networks, and argue that results indicate a strong form of the linguistic structuring thesis is true: Internal representational systems recapitulate significant linguistic structure, even on a connectionist account of mental representation. I conclude by sketching how my conclusion can nonetheless be viewed as consistent with and complimentary to an embedded/embodied account of the role of linguistic structure in cognition. (shrink)

In this introduction to the special issue on time and viewpoint in narrative discourse, we highlight the central contributions of the issue concerning the relation between the linguistic construal and cognitive representation of time and viewpoint. We explain how linguistic and gestural cues guide the representation of narrative time progression and argue that this representation involves various cognitive operations regulating the alignment between the viewpoints of narrator, addressee, and narrative characters. These operations are steered by a variety of (...) linguistic phenomena, including verb tense, adverbs, demonstratives, reduplication and negation, as well as body partitioning. We discuss how genre characteristics influence the relation between the linguistic and cognitive representation of time and viewpoint. Finally, we explain how the analyses presented in the various papers both demonstrate and clarify how the cognitive representation of time in narrative discourse relies on the human capacity to simultaneously manage multiple viewpoints, leading to the conclusion that time and viewpoint are closely related in the representation of narrative discourse. (shrink)

I argue that, pace Chomsky (2000, 2003), standard theories of linguistic competence are committed to taking talk of representations seriously, in particular, to recognizing that the “of x” clause that invariably follows “representation” is a way of specifying that representation’s intentional content. One reason to insist upon intentional content in such cases is that the “x” in “of x” may not exist (as in "of Zeus"). This issue is especially relevant to linguistics since, recapitulating considerations raised by many (...) linguists, I go on to argue that most of the SLEs themselves seldom, if ever exist: it is doubtful there are many, if any, tokens of them in space and time; indeed, their existence is by and large inessential to the needs of either communication or serious linguistic theory. All that linguistic theory requires to be real in this regard are the representations, presumably entokened in people’s brains, understood, however, in terms of their intentional contents. (shrink)