1,410 research outputs found
The Epistemic Value of Resonance: Intuitive Thinking in Theoretical Understanding
We commonly say that an explanation for something we do not quite understand ‘resonates’. And we seem to take the resonance of the explanation to count epistemically in its favor. What is resonance and what is its epistemic value? I propose that resonance is a psychological state in which a consciously considered explanation coheres with the unconscious representational content in the mind of an individual, and that this psychological state is metacognitively signaled by a feeling which we also call ‘resonance’. This account of resonance implies that theoretical understanding, rather than knowledge, is the epistemic domain of its functioning. That is, when an explanation resonates, the usual case is that a consciously considered explanatory framework coheres with a rich, unconscious representational nexus associated with the object purportedly explained.
I pursue the question of the value of resonance by developing the features of theoretical understanding. Theoretical understanding of an object, I take it, is when an individual grasps an accurate explanatory framework for that object. Hence, understanding is normed by both accuracy and grasping. Accuracy, however, is secured through warrant. Resonance, I argue, can increase one’s warrant, but not very much. Grasping, on the other hand, is a stop-and-go process of integrating explanations and representational content in long-term memory. Resonance, I argue, improves grasping by ensuring coherence and motivating persistence. Further, resonance seems to be practically necessary to theoretical understanding, insofar as understanding aims toward an aspirational mastery. Resonance enables us to invest cognitive resources in explanatory frameworks we do not yet understand and it prevents us from becoming rigidly attached to a familiar but failing explanatory framework.
I conclude by addressing three worries about the epistemic value of resonance: (1) that the feeling of resonance cannot be distinguished from similar, non-epistemic feelings, (2) that the pleasantness of this feeling conflicts with the accuracy norm for understanding, and (3) that an explanatory framework might resonate with false unconscious beliefs, thus inhibiting accuracy in one’s understanding. Of these, the last is the most worrisome and suggests that attuning to resonance is only one part of a virtuous epistemic life
Driving Context into Text-to-Text Privatization
\textit{Metric Differential Privacy} enables text-to-text privatization by
adding calibrated noise to the vector of a word derived from an embedding space
and projecting this noisy vector back to a discrete vocabulary using a nearest
neighbor search. Since words are substituted without context, this mechanism is
expected to fall short at finding substitutes for words with ambiguous
meanings, such as \textit{'bank'}. To account for these ambiguous words, we
leverage a sense embedding and incorporate a sense disambiguation step prior to
noise injection. We encompass our modification to the privatization mechanism
with an estimation of privacy and utility. For word sense disambiguation on the
\textit{Words in Context} dataset, we demonstrate a substantial increase in
classification accuracy by
Broadening the Horizon of Adversarial Attacks in Deep Learning
152 p.Los modelos de Aprendizaje Automático como las Redes Neuronales Profundas son actualmente el núcleo de una amplia gama de tecnologÃas aplicadas en tareas crÃticas, como el reconocimiento facial o la conducción autónoma, en las que tanto la capacidad predictiva como la fiabilidad son requisitos fundamentales. Sin embargo, estos modelos pueden ser fácilmente engañados por inputs manipulados deforma imperceptible para el ser humano, denominados ejemplos adversos (adversarial examples), lo que implica una brecha de seguridad que puede ser explotada por un atacante con fines ilÃcitos. Dado que estas vulnerabilidades afectan directamente a la integridad y fiabilidad de múltiples sistemas que,progresivamente, están siendo desplegados en aplicaciones del mundo real, es crucial determinar el alcance de dichas vulnerabilidades para poder garantizar asà un uso más responsable, informado y seguro de esos sistemas. Por estos motivos, esta tesis doctoral tiene como objetivo principal investigar nuevas nociones de ataques adversos y vulnerabilidades en las Redes Neuronales Profundas. Como resultado de esta investigación, a lo largo de esta tesis se exponen nuevos paradigmas de ataque que exceden o amplÃan las capacidades de los métodos actualmente disponibles en la literatura, ya que son capaces de alcanzar objetivos más generales, complejos o ambiciosos. Al mismo tiempo, se exponen nuevas brechas de seguridad en casos de uso y escenarios en los que las consecuencias de los ataques adversos no habÃan sido investigadas con anterioridad. Nuestro trabajo también arroja luz sobre diferentes propiedades de estos modelos que los hacen más vulnerables a los ataques adversos, contribuyendo a una mejor comprensión de estos fenómenos
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Machine Learning Algorithm for the Scansion of Old Saxon Poetry
Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools
deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We
implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon
and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and
we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm
reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested
the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that
the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input
verses
Fitting Pragmatics into the Human Mind: A philosophical investigation of the Pragmatics Module Hypothesis
This thesis focuses on the hypothesis that pragmatic understanding is underpinned by a mental module closely related to the ability to interpret others’ behaviors by inferring underlying mental states, also called ‘mindreading’. First, it aims at evaluating the plausibility of this hypothesis in light of the available data in the empirical literature by drawing on the argumentative toolbox of the philosophy of mind and language. Second, it aims at developing this hypothesis by addressing its main theoretical and empirical challenges.
In Chapter One, I outline a historical overview of the different declinations of the modularity hypothesis in cognitive science, with a focus on early works in cognitive pragmatics and Theory of Mind research.
In Chapter Two, I provide a comprehensive theoretical analysis of the Pragmatics Module Hypothesis by focusing on the central tenets of Relevance Theory.
In Chapter Three, I explore the idea of pragmatics as a ‘sub-module’ of Theory of Mind from an empirical perspective by surveying the current state of the art in experimental and clinical pragmatics, thus ‘clearing up’ the recent controversy on the modularity of pragmatics from some misconceptions and empirical predictions which do not follow from the Pragmatics Module Hypothesis.
In Chapter Four, I provide a novel cognitive framework for the modular view of pragmatics by evaluating the significance of research on ostensive communication in infancy with respect to the hypothesis of an early-developing modular heuristic for interpreting communicative behaviors.
Chapters Five and Six both focus on the several ‘developmental dilemmas’ that must be confronted by intentional-inferential accounts of infant communication like the one endorsed in the present thesis, which will be disentangled, analyzed, and addressed by evaluating several possible solutions. In these two chapters, I show how the cognitive framework offered in Chapter Four can be employed and further extended to deal with such developmental dilemmas from a renewed modular perspective
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