1,711 research outputs found

    Automatic and Human-AI Interactive Text Generation

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    In this tutorial, we focus on text-to-text generation, a class of natural language generation (NLG) tasks, that takes a piece of text as input and then generates a revision that is improved according to some specific criteria (e.g., readability or linguistic styles), while largely retaining the original meaning and the length of the text. This includes many useful applications, such as text simplification, paraphrase generation, style transfer, etc. In contrast to text summarization and open-ended text completion (e.g., story), the text-to-text generation tasks we discuss in this tutorial are more constrained in terms of semantic consistency and targeted language styles. This level of control makes these tasks ideal testbeds for studying the ability of models to generate text that is both semantically adequate and stylistically appropriate. Moreover, these tasks are interesting from a technical standpoint, as they require complex combinations of lexical and syntactical transformations, stylistic control, and adherence to factual knowledge, -- all at once. With a special focus on text simplification and revision, this tutorial aims to provide an overview of the state-of-the-art natural language generation research from four major aspects -- Data, Models, Human-AI Collaboration, and Evaluation -- and to discuss and showcase a few significant and recent advances: (1) the use of non-retrogressive approaches; (2) the shift from fine-tuning to prompting with large language models; (3) the development of new learnable metric and fine-grained human evaluation framework; (4) a growing body of studies and datasets on non-English languages; (5) the rise of HCI+NLP+Accessibility interdisciplinary research to create real-world writing assistant systems.Comment: To appear at ACL 2024, Tutoria

    The Anatomy of a Grid portal

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    In this paper we introduce a new way to deal with Grid portals referring to our implementation. L-GRID is a light portal to access the EGEE/EGI Grid infrastructure via Web, allowing users to submit their jobs from a common Web browser in a few minutes, without any knowledge about the Grid infrastructure. It provides the control over the complete lifecycle of a Grid Job, from its submission and status monitoring, to the output retrieval. The system, implemented as client-server architecture, is based on the Globus Grid middleware. The client side application is based on a java applet; the server relies on a Globus User Interface. There is no need of user registration on the server side, and the user needs only his own X.509 personal certificate. The system is user-friendly, secure (it uses SSL protocol, mechanism for dynamic delegation and identity creation in public key infrastructures), highly customizable, open source, and easy to install. The X.509 personal certificate does not get out from the local machine. It allows to reduce the time spent for the job submission, granting at the same time a higher efficiency and a better security level in proxy delegation and management.Comment: 6 page

    SONIA: an immersive customizable virtual reality system for the education and exploration of brain networks

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    While mastery of neuroanatomy is important for the investigation of the brain, there is an increasing interest in exploring the neural pathways to better understand the roles of neural circuitry in brain functions. To tackle the limitations of traditional 2D-display-based neuronavigation software in intuitively visualizing complex 3D anatomies, several virtual reality (VR) and augmented reality (AR) solutions have been proposed to facilitate neuroanatomical education. However, with the increasing knowledge on brain connectivity and the functioning of the sub-systems, there is still a lack of similar software solutions for the education and exploration of these topics, which demand more elaborate visualization and interaction strategies. To address this gap, we designed the immerSive custOmizable Neuro learnIng plAform (SONIA), a novel user-friendly VR software system with a multi-scale interaction paradigm that allows flexible customization of learning materials. With both quantitative and qualitative evaluations through user studies, the proposed system is shown to have high usability, attractive visual design, and good educational value. As the first immersive system that integrates customizable design and detailed narratives of the brain sub-systems for the education of neuroanatomy and brain connectivity, SONIA showcases new potential directions and provides valuable insights regarding medical learning and exploration in VR

    Perspectives on Case-based Multimedia Web Projects in Science

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    This article discusses the merits of case-based learning in an interactive online environment. Researchers used both qualitative and quantitative research over a 2-year period to examine the learning that occurred in a high school context when students were engaged in a case-based multimedia project. Part of the Case It! project, students played both the role of laboratory technician performing and presenting research as well as professionals using the information in their practice. Students were required to use three types of simulation software developed exclusively for the Case It! project. Results were measured using both pre- and post-tests, artifacts students created such as Web posters, records of Internet conferences, and interviews from both the students and the teacher involved in this project. Researches found the online format of the lesson fostered a higher level of questioning and problem solving skills, as well as extended explanations and discussions of ethics in science. Educational levels: Graduate or professional

    Visual exploration of semantic-web-based knowledge structures

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    Humans have a curious nature and seek a better understanding of the world. Data, in- formation, and knowledge became assets of our modern society through the information technology revolution in the form of the internet. However, with the growing size of accumulated data, new challenges emerge, such as searching and navigating in these large collections of data, information, and knowledge. The current developments in academic and industrial contexts target the corresponding challenges using Semantic Web techno- logies. The Semantic Web is an extension of the Web and provides machine-readable representations of knowledge for various domains. These machine-readable representations allow intelligent machine agents to understand the meaning of the data and information; and enable additional inference of new knowledge. Generally, the Semantic Web is designed for information exchange and its processing and does not focus on presenting such semantically enriched data to humans. Visualizations support exploration, navigation, and understanding of data by exploiting humans’ ability to comprehend complex data through visual representations. In the context of Semantic- Web-Based knowledge structures, various visualization methods and tools are available, and new ones are being developed every year. However, suitable visualizations are highly dependent on individual use cases and targeted user groups. In this thesis, we investigate visual exploration techniques for Semantic-Web-Based knowledge structures by addressing the following challenges: i) how to engage various user groups in modeling such semantic representations; ii) how to facilitate understanding using customizable visual representations; and iii) how to ease the creation of visualizations for various data sources and different use cases. The achieved results indicate that visual modeling techniques facilitate the engagement of various user groups in ontology modeling. Customizable visualizations enable users to adjust visualizations to the current needs and provide different views on the data. Additionally, customizable visualization pipelines enable rapid visualization generation for various use cases, data sources, and user group

    Graphical microcode simulator with a reconfigurable datapath

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    Microcode is a symbolic way to simplify control design that allows changing, testing and updating the control unit of processors. By changing the microcode, the same datapath can be used for an entirely different application, such as supporting a completely different instruction set. For these reasons, a majority of control units in modern day processors are microcoded. The object was to investigate and implement a graphical microcode simulator with a reconfigurable datapath and microcode format. By allowing a wide configuration of the datapath, many types of logical processors can be designed and simulated. The resulting implemented simulator is able to fill the void in microprogramming tools since there are no graphical microcode simulators that allow such customization of the datapath. The customization of the datapath goes beyond allowing different files specifying the datapath, it allows the datapath to be created and modified using the graphical interface.This tool is able to be used to design and simulate general-purpose processors and application specific processors through datapath and microcode configurations. In the academic setting, this tool provides easier microcode testing through verification on the instruction level for instructors and provide simulation debugging through code tracing and breakpoints for students
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