RELATION BETWEEN THE REACTION TIME AND THE AMPLITUDE CHANGES OF THE H-REFLEX IN CASE OF SUCCESSIVE PLANTAR FLEXION OF THE FEET PERFORMED UNDER DIFFERENT EXPERIMENTAL CONDITIONS

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Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

How healthcare systems are experienced by autistic adults in the United Kingdom: A meta-ethnography

Autistic adults are at increased risk of both mental and physical health difficulties, and yet can face barriers to accessing healthcare. A meta-ethnographic approach was used to conduct a review of the existing literature regarding autistic adults’ experiences of accessing healthcare. Four databases were systematically searched for qualitative and mixed-method studies reporting on the experiences of autistic adults without a co-occurring learning disability accessing adult healthcare services within the United Kingdom. Fifteen studies met the inclusion criteria, and seven steps were used to systematically extract the data and then generate novel themes. Three superordinate themes were identified: Professionals’ lack of knowledge can be damaging, Need to reduce processing demands and Adaptation to improve engagement. This review highlights the wide-reaching damaging impact misdiagnosis, inadequate or inappropriate treatment, overwhelming environments and inaccessible systems can have on the well-being and ability of autistic adults to engage with treatment. The lack of autism knowledge and understanding experienced in interactions with healthcare professionals, along with autistic adult’s own communication and sensory processing differences, demonstrates the need for widely delivered training co-produced with autistic adults alongside bespoke and person-centred adaptations

Concepts in Animal Parasitology, Chapter 56: Strongyloidea and Trichostrongyloidea (Superfamilies): Bursate Nematodes

Chapter 56 in Concepts in Animal Parasitology on the bursate nematodes in the superfamilies Strongyloidea and Trichostrongyloidea by Larry S. Roberts, John J. Janovy, Jr., Steven Nadler, Valentin Radev, and Scott L. Gardner. 2024. S. L. Gardner and S. A. Gardner, editors. Zea Books, Lincoln, Nebraska, United States. doi: 10.32873/unl.dc.ciap05

Using Synchronic and Diachronic Relations for Summarizing Multiple Documents Describing Evolving Events

In this paper we present a fresh look at the problem of summarizing evolving events from multiple sources. After a discussion concerning the nature of evolving events we introduce a distinction between linearly and non-linearly evolving events. We present then a general methodology for the automatic creation of summaries from evolving events. At its heart lie the notions of Synchronic and Diachronic cross-document Relations (SDRs), whose aim is the identification of similarities and differences between sources, from a synchronical and diachronical perspective. SDRs do not connect documents or textual elements found therein, but structures one might call messages. Applying this methodology will yield a set of messages and relations, SDRs, connecting them, that is a graph which we call grid. We will show how such a grid can be considered as the starting point of a Natural Language Generation System. The methodology is evaluated in two case-studies, one for linearly evolving events (descriptions of football matches) and another one for non-linearly evolving events (terrorist incidents involving hostages). In both cases we evaluate the results produced by our computational systems.Comment: 45 pages, 6 figures. To appear in the Journal of Intelligent Information System

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages without incurring prohibitively large costs, it is desirable to adapt BLOOM to new languages not seen during pretraining. In this work, we apply existing language adaptation strategies to BLOOM and benchmark its zero-shot prompting performance on eight new languages in a resource-constrained setting. We find language adaptation to be effective at improving zero-shot performance in new languages. Surprisingly, we find that adapter-based finetuning is more effective than continued pretraining for large models. In addition, we discover that prompting performance is not significantly affected by language specifics, such as the writing system. It is primarily determined by the size of the language adaptation data. We also add new languages to BLOOMZ, which is a multitask finetuned version of BLOOM capable of following task instructions zero-shot. We find including a new language in the multitask fine-tuning mixture to be the most effective method to teach BLOOMZ a new language. We conclude that with sufficient training data language adaptation can generalize well to diverse languages. Our code is available at https://github.com/bigscience-workshop/multilingual-modeling

Rethinking summarization and storytelling for modern social multimedia

Traditional summarization initiatives have been focused on specific types of documents such as articles, reviews, videos, image feeds, or tweets, a practice which may result in pigeonholing the summarization task in the context of modern, content-rich multimedia collections. Consequently, much of the research to date has revolved around mostly toy problems in narrow domains and working on single-source media types. We argue that summarization and story generation systems need to re-focus the problem space in order to meet the information needs in the age of user-generated content in different formats and languages. Here we create a framework for flexible multimedia storytelling. Narratives, stories, and summaries carry a set of challenges in big data and dynamic multi-source media that give rise to new research in spatial-temporal representation, viewpoint generation, and explanatio

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

PromptSource is a system for creating, sharing, and using natural language prompts. Prompts are functions that map an example from a dataset to a natural language input and target output. Using prompts to train and query language models is an emerging area in NLP that requires new tools that let users develop and refine these prompts collaboratively. PromptSource addresses the emergent challenges in this new setting with (1) a templating language for defining data-linked prompts, (2) an interface that lets users quickly iterate on prompt development by observing outputs of their prompts on many examples, and (3) a community-driven set of guidelines for contributing new prompts to a common pool. Over 2,000 prompts for roughly 170 datasets are already available in PromptSource. PromptSource is available at https://github.com/bigscience-workshop/promptsource.Comment: ACL 2022 Dem