527 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Comparing the production of a formula with the development of L2 competence

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    This pilot study investigates the production of a formula with the development of L2 competence over proficiency levels of a spoken learner corpus. The results show that the formula in beginner production data is likely being recalled holistically from learners’ phonological memory rather than generated online, identifiable by virtue of its fluent production in absence of any other surface structure evidence of the formula’s syntactic properties. As learners’ L2 competence increases, the formula becomes sensitive to modifications which show structural conformity at each proficiency level. The transparency between the formula’s modification and learners’ corresponding L2 surface structure realisations suggest that it is the independent development of L2 competence which integrates the formula into compositional language, and ultimately drives the SLA process forward

    ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing

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    Given the rapid ascent of large language models (LLMs), we study the question: (How) can large language models help in reviewing of scientific papers or proposals? We first conduct some pilot studies where we find that (i) GPT-4 outperforms other LLMs (Bard, Vicuna, Koala, Alpaca, LLaMa, Dolly, OpenAssistant, StableLM), and (ii) prompting with a specific question (e.g., to identify errors) outperforms prompting to simply write a review. With these insights, we study the use of LLMs (specifically, GPT-4) for three tasks: 1. Identifying errors: We construct 13 short computer science papers each with a deliberately inserted error, and ask the LLM to check for the correctness of these papers. We observe that the LLM finds errors in 7 of them, spanning both mathematical and conceptual errors. 2. Verifying checklists: We task the LLM to verify 16 closed-ended checklist questions in the respective sections of 15 NeurIPS 2022 papers. We find that across 119 {checklist question, paper} pairs, the LLM had an 86.6% accuracy. 3. Choosing the "better" paper: We generate 10 pairs of abstracts, deliberately designing each pair in such a way that one abstract was clearly superior than the other. The LLM, however, struggled to discern these relatively straightforward distinctions accurately, committing errors in its evaluations for 6 out of the 10 pairs. Based on these experiments, we think that LLMs have a promising use as reviewing assistants for specific reviewing tasks, but not (yet) for complete evaluations of papers or proposals

    Approximation in Morphology

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    This Special Issue "Approximation in Morphology" has been collated from peer-reviewed papers presented at the ApproxiMo 'discontinuous' workshop (2022), which was held online between December 2021 and May 2022, and organized by Francesca Masini (Bologna), Muriel Norde (Berlin) and Kristel Van Goethem (Louvain)

    Applications of graph theory to wireless networks and opinion analysis

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    La teoría de grafos es una rama importante dentro de la matemática discreta. Su uso ha aumentado recientemente dada la conveniencia de los grafos para estructurar datos, para analizarlos y para generarlos a través de modelos. El objetivo de esta tesis es aplicar teoría de grafos a la optimización de redes inalámbricas y al análisis de opinión. El primer conjunto de contribuciones de esta tesis versa sobre la aplicación de teoría de grafos a redes inalámbricas. El rendimiento de estas redes depende de la correcta distribución de canales de frecuencia en un espacio compartido. Para optimizar estas redes se proponen diferentes técnicas, desde la aplicación de heurísticas como simulated annealing a la negociación automática. Cualquiera de estas técnicas requiere un modelo teórico de la red inalámbrica en cuestión. Nuestro modelo de redes Wi-Fi utiliza grafos geométricos para este propósito. Los vértices representan los dispositivos de la red, sean clientes o puntos de acceso, mientras que las aristas representan las señales entre dichos dispositivos. Estos grafos son de tipo geométrico, por lo que los vértices tienen posición en el espacio, y las aristas tienen longitud. Con esta estructura y la aplicación de un modelo de propagación y de uso, podemos simular redes inalámbricas y contribuir a su optimización. Usando dicho modelo basado en grafos, hemos estudiado el efecto de la interferencia cocanal en redes Wi-Fi 4 y mostramos una mejora de rendimiento asociada a la técnica de channel bonding cuando se usa en regiones donde hay por lo menos 13 canales disponibles. Por otra parte, en esta tesis doctoral hemos aplicado teoría de grafos al análisis de opinión dentro de la línea de investigación de SensoGraph, un método con el que se realiza un análisis de opinión sobre un conjunto de elementos usando grafos de proximidad, lo que permite manejar grandes conjuntos de datos. Además, hemos desarrollado un método de análisis de opinión que emplea la asignación manual de aristas y distancias en un grafo para estudiar la similaridad entre las muestras dos a dos. Adicionalmente, se han explorado otros temas sin relación con los grafos, pero que entran dentro de la aplicación de las matemáticas a un problema de la ingeniería telemática. Se ha desarrollado un sistema de votación electrónica basado en mixnets, secreto compartido de Shamir y cuerpos finitos. Dicha propuesta ofrece un sistema de verificación numérico novedoso a la vez que mantiene las propiedades esenciales de los sistemas de votación

    The extended codes of a family of reversible MDS cyclic codes

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    A linear code with parameters [n,k,nk+1][n, k, n-k+1] is called a maximum distance separable (MDS for short) code. A linear code with parameters [n,k,nk][n, k, n-k] is said to be almost maximum distance separable (AMDS for short). A linear code is said to be near maximum distance separable (NMDS for short) if both the code and its dual are AMDS. MDS codes are very important in both theory and practice. There is a classical construction of a [q+1,2u1,q2u+3][q+1, 2u-1, q-2u+3] MDS code for each uu with 1uq+121 \leq u \leq \lfloor\frac{q+1}2\rfloor, which is a reversible and cyclic code. The objective of this paper is to study the extended codes of this family of MDS codes. Two families of MDS codes and several families of NMDS codes are obtained. The NMDS codes have applications in finite geometry, cryptography and distributed and cloud data storage systems. The weight distributions of some of the extended codes are determined

    Coding for Privacy in Distributed Computing

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    I et distribuert datanettverk samarbeider flere enheter for å løse et problem. Slik kan vi oppnå mer enn summen av delene: samarbeid gjør at problemet kan løses mer effektivt, og samtidig blir det mulig å løse problemer som hver enkelt enhet ikke kan løse på egen hånd. På den annen side kan enheter som bruker veldig lang tid på å fullføre sin oppgave øke den totale beregningstiden betydelig. Denne såkalte straggler-effekten kan oppstå som følge av tilfeldige hendelser som minnetilgang og oppgaver som kjører i bakgrunnen på de ulike enhetene. Straggler-problemet blokkerer vanligvis hele beregningen siden alle enhetene må vente på at de treigeste enhetene blir ferdige. Videre kan deling av data og delberegninger mellom de ulike enhetene belaste kommunikasjonsnettverket betydelig. Spesielt i et trådløst nettverk hvor enhetene må dele en enkelt kommunikasjonskanal, for eksempel ved beregninger langs kanten av et nettverk (såkalte kantberegninger) og ved føderert læring, blir kommunikasjonen ofte flaskehalsen. Sist men ikke minst gir deling av data med upålitelige enheter økt bekymring for personvernet. En som ønsker å bruke et distribuert datanettverk kan være skeptisk til å dele personlige data med andre enheter uten å beskytte sensitiv informasjon tilstrekkelig. Denne avhandlingen studerer hvordan ideer fra kodeteori kan dempe straggler-problemet, øke effektiviteten til kommunikasjonen og garantere datavern i distribuert databehandling. Spesielt gir del A en innføring i kantberegning og føderert læring, to populære instanser av distribuert databehandling, lineær regresjon, et vanlig problem som kan løses ved distribuert databehandling, og relevante ideer fra kodeteori. Del B består av forskningsartikler skrevet innenfor rammen av denne avhandlingen. Artiklene presenterer metoder som utnytter ideer fra kodeteori for å redusere beregningstiden samtidig som datavernet ivaretas ved kantberegninger og ved føderert læring. De foreslåtte metodene gir betydelige forbedringer sammenlignet med tidligere metoder i litteraturen. For eksempel oppnår en metode fra artikkel I en 8%-hastighetsforbedring for kantberegninger sammenlignet med en nylig foreslått metode. Samtidig ivaretar vår metode datavernet, mens den metoden som vi sammenligner med ikke gjør det. Artikkel II presenterer en metode som for noen brukstilfeller er opp til 18 ganger raskere for føderert læring sammenlignet med tidligere metoder i litteraturen.In a distributed computing network, multiple devices combine their resources to solve a problem. Thereby the network can achieve more than the sum of its parts: cooperation of the devices can enable the devices to compute more efficiently than each device on its own could and even enable the devices to solve a problem neither of them could solve on its own. However, devices taking exceptionally long to finish their tasks can exacerbate the overall latency of the computation. This so-called straggler effect can arise from random effects such as memory access and tasks running in the background of the devices. The effect typically stalls the whole network because most devices must wait for the stragglers to finish. Furthermore, sharing data and results among devices can severely strain the communication network. Especially in a wireless network where devices have to share a common channel, e.g., in edge computing and federated learning, the communication links often become the bottleneck. Last but not least, offloading data to untrusted devices raises privacy concerns. A participant in the distributed computing network might be weary of sharing personal data with other devices without adequately protecting sensitive information. This thesis analyses how ideas from coding theory can mitigate the straggler effect, reduce the communication load, and guarantee data privacy in distributed computing. In particular, Part A gives background on edge computing and federated learning, two popular instances of distributed computing, linear regression, a common problem to be solved by distributed computing, and the specific ideas from coding theory that are proposed to tackle the problems arising in distributed computing. Part B contains papers on the research performed in the framework of this thesis. The papers propose schemes that combine the introduced coding theory ideas to minimize the overall latency while preserving data privacy in edge computing and federated learning. The proposed schemes significantly outperform state-of-the-art schemes. For example, a scheme from Paper I achieves an 8% speed-up for edge computing compared to a recently proposed non-private scheme while guaranteeing data privacy, whereas the schemes from Paper II achieve a speed-up factor of up to 18 for federated learning compared to current schemes in the literature for considered scenarios.Doktorgradsavhandlin

    Lifting iso-dual algebraic geometry codes

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    In this work we investigate the problem of producing iso-dual algebraic geometry (AG) codes over a finite field Fq\mathbb{F}_q with qq elements. Given a finite separable extension M/F\mathcal{M}/\mathcal{F} of function fields and an iso-dual AG-code C\mathcal{C} defined over F\mathcal{F}, we provide a general method to lift the code C\mathcal{C} to another iso-dual AG-code C~\tilde{\mathcal{C}} defined over M\mathcal{M} under some assumptions on the parity of the involved different exponents. We apply this method to lift iso-dual AG-codes over the rational function field to elementary abelian pp-extensions, like the maximal function fields defined by the Hermitian, Suzuki, and one covered by the GGSGGS function field. We also obtain long binary and ternary iso-dual AG-codes defined over cyclotomic extensions.Comment: 26 pages, 3 figure

    On Galois self-orthogonal algebraic geometry codes

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    Galois self-orthogonal (SO) codes are generalizations of Euclidean and Hermitian SO codes. Algebraic geometry (AG) codes are the first known class of linear codes exceeding the Gilbert-Varshamov bound. Both of them have attracted much attention for their rich algebraic structures and wide applications in these years. In this paper, we consider them together and study Galois SO AG codes. A criterion for an AG code being Galois SO is presented. Based on this criterion, we construct several new classes of maximum distance separable (MDS) Galois SO AG codes from projective lines and several new classes of Galois SO AG codes from projective elliptic curves, hyper-elliptic curves and hermitian curves. In addition, we give an embedding method that allows us to obtain more MDS Galois SO codes from known MDS Galois SO AG codes.Comment: 18paper
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