15,650 research outputs found
Less is More: A Lightweight and Robust Neural Architecture for Discourse Parsing
Complex feature extractors are widely employed for text representation
building. However, these complex feature extractors make the NLP systems prone
to overfitting especially when the downstream training datasets are relatively
small, which is the case for several discourse parsing tasks. Thus, we propose
an alternative lightweight neural architecture that removes multiple complex
feature extractors and only utilizes learnable self-attention modules to
indirectly exploit pretrained neural language models, in order to maximally
preserve the generalizability of pre-trained language models. Experiments on
three common discourse parsing tasks show that powered by recent pretrained
language models, the lightweight architecture consisting of only two
self-attention layers obtains much better generalizability and robustness.
Meanwhile, it achieves comparable or even better system performance with fewer
learnable parameters and less processing time
Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition
Due to the absence of explicit connectives, implicit discourse relation
recognition (IDRR) remains a challenging task in discourse analysis. The
critical step for IDRR is to learn high-quality discourse relation
representations between two arguments. Recent methods tend to integrate the
whole hierarchical information of senses into discourse relation
representations for multi-level sense recognition. Nevertheless, they
insufficiently incorporate the static hierarchical structure containing all
senses (defined as global hierarchy), and ignore the hierarchical sense label
sequence corresponding to each instance (defined as local hierarchy). For the
purpose of sufficiently exploiting global and local hierarchies of senses to
learn better discourse relation representations, we propose a novel GLobal and
LOcal Hierarchy-aware Contrastive Framework (GLOF), to model two kinds of
hierarchies with the aid of contrastive learning. Experimental results on the
PDTB dataset demonstrate that our method remarkably outperforms the current
state-of-the-art model at all hierarchical levels.Comment: 13 pages, 10 figure
Learning Explicit and Implicit Arabic Discourse Relations.
We propose in this paper a supervised learning approach to identify discourse relations in Arabic texts. To our knowledge, this work represents the first attempt to focus on both explicit and implicit relations that link adjacent as well as non adjacent Elementary Discourse Units (EDUs) within the Segmented Discourse Representation Theory (SDRT). We use the Discourse Arabic Treebank corpus (D-ATB) which is composed of newspaper documents extracted from the syntactically annotated Arabic Treebank v3.2 part3 where each document is associated with complete discourse graph according to the cognitive principles of SDRT. Our list of discourse relations is composed of a three-level hierarchy of 24 relations grouped into 4 top-level classes. To automatically learn them, we use state of the art features whose efficiency has been empirically proved. We investigate how each feature contributes to the learning process. We report our experiments on identifying fine-grained discourse relations, mid-level classes and also top-level classes. We compare our approach with three baselines that are based on the most frequent relation, discourse connectives and the features used by Al-Saif and Markert (2011). Our results are very encouraging and outperform all the baselines with an F-score of 78.1% and an accuracy of 80.6%
Academic literacies twenty years on: a community-sourced literature review
In 1998, the paper âStudent writing in higher education: an academic literacies approachâ by Mary Lea and Brian Street reinvigorated debate concerning âwhat it means to be academically literateâ (1998, p.158). It proposed a new way of examining how students learn at university and introduced the term âacademic literaciesâ. Subsequently, a body of literature has emerged reflecting the significant theoretical and practical impact Lea and Streetâs paper has had on a range of academic and professional fields. This literature review covers articles selected by colleagues in our professional communities of the Association for Learning Development in Higher Education (ALDinHE), BALEAP the global forum for English for Academic Purposes (EAP) professionals, and the European Association of Teachers of Academic Writing (EATAW). As a community-sourced literature review, this text brings together reviews of wide range of texts and a diverse range of voices reflecting a multiplicity of perspectives and understandings of academic literacies. We have organised the material according to the themes: Modality, Identity, Focus on text, Implications for research, and Implications for practice. We conclude with observations relevant to these themes, which we hope will stimulate further debate, research and professional collaborations between our members and subscribers
Internationalisation of HE in the UK: 'Where are we now and where might we go?'
This paper is based on a literature review commissioned by the Higher Education Academy in 2006 which aimed to identify existing published literature and current practices of direct relevance to the Internationalisation of Higher Education in the UK. The review was based on the assumption that a range of concerns exists, that there are emerging issues and that there are inconsistencies and gaps in the literature. The project focused on a number of questions including: what working definitions of internationalisation of higher education are in currency? what meanings are attributed to internationalisation of the curriculum? what models for institutional internationalisation are emerging? and, what curriculum models are emerging/being adopted? The literature trawl identified in excess of 300 international sources of relevance, of which, more that 100 originated in the UK. This paper draws on the analysis of these sources to determine âwhere we areâ in the UK in comparison with our Western counterparts, particularly HEIs based in Australia
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing
Many natural language processing (NLP) tasks are naturally imbalanced, as
some target categories occur much more frequently than others in the real
world. In such scenarios, current NLP models still tend to perform poorly on
less frequent classes. Addressing class imbalance in NLP is an active research
topic, yet, finding a good approach for a particular task and imbalance
scenario is difficult.
With this survey, the first overview on class imbalance in deep-learning
based NLP, we provide guidance for NLP researchers and practitioners dealing
with imbalanced data. We first discuss various types of controlled and
real-world class imbalance. Our survey then covers approaches that have been
explicitly proposed for class-imbalanced NLP tasks or, originating in the
computer vision community, have been evaluated on them. We organize the methods
by whether they are based on sampling, data augmentation, choice of loss
function, staged learning, or model design. Finally, we discuss open problems
such as dealing with multi-label scenarios, and propose systematic benchmarking
and reporting in order to move forward on this problem as a community
How the couple is observing the couple observing
Der Zweck der vorliegenden Studie besteht darin, die These zu ĂŒberprĂŒfen, ob das analytische Paar eine selbststĂ€ndige Einheit ist. Die Beobachtung, definiert als Etwas, das einen Unterschied im Umfeld des Anderen macht, ist eine Handlung, die vom Analysten, dem Patienten und dem analytischen Paar durchgefĂŒhrt wird. Die zentrale Frage beschĂ€ftigt sich mit der Art und Weise, in der sich die analytische Sitzung aus einer triadischen Perspektive entfaltet: Kann das analytische Paar in seinem eigenen Umfeld einen Unterschied machen und sich zum Zweck der Anpassung verwandeln? Es wird eine mathematisch modellierte Herangehensweise benutzt, die davon ausgeht: âsind diese funktionell Ă€quivalent oder unterschiedlich?â. Das neue Modell bietet eine binĂ€r geschriebene âFormâ, von âsymmetrischer Differenzâ bestimmt, wĂ€hrend jegliche selbststĂ€ndige IdentitĂ€t zweidimensional ist, der Sprecher und der Zuhörer. Es wird gezeigt, dass Beobachtung mit Rekursion verbunden ist. âBeobachtungâ, so wie diese vom Paar ausgeĂŒbt wird, gestaltet permanent neue Unterschiede in dem Umfeld, als Folge der ĂuĂerungen, die AblĂ€ufe von ĂuĂerungen widerspiegeln. Rekursion und Komplexifikation beantworten wie das Paar neue Unterschiede macht und diese âBeobachtungenâ umwandelt und sich auf das was vor sich geht, anpasst. Das Paar entfaltet sich demnach: âweniger Ordnung â Schwankungen â mehr Ordnungâ und bestĂ€tigt die theoretisierte Form des Prozesses: âRekursion â Komplexifikation â VorgĂ€nge auf der nĂ€chsten Ebeneâ. Paar zeichnet Unterschiede in seinem Umfeld auf, indem es sich selbst widerspiegelt. Es wird gezeigt, dass VorgĂ€nge auf der nĂ€chsten Ebene aus einer Abfolge von selbstgespiegelten VorgĂ€ngen hervorgehen. Eine derartige Herangehensweise bedeutet, (empirisch) zu zeigen, ob diese Perspektive beobachtbare Elemente bietet und wie diese fĂŒr die Art und Weise, in der der analytische Vorgang betrachtet wird, von Bedeutung sind.The aim of the present study is to test the idea that the analytic couple is an autonomous entity. Observing, defined as making distinctions in oneâs environment, is seen as an action performed by the analyst, the patient and by the analytic couple. The main question addresses how the analytic session unfolds in a triadic view: Is the analytic couple able to make distinctions in its own environment and transform for adapting?
A mathematical inspired modelling approach is employed, that starts from: âare they functionally equivalent or different?â. The new model provides a binary written âformâ, governed by âsymmetric differenceâ, while any autonomous entity is bidimensional, involving the speaker and the listener.
It is shown that observing involves recursion. So, âobservingâ as performed by the couple is ongoingly devising new distinctions in the environment, as sequences of utterances mirroring sequence of utterances. Recursion and complexification answer to how the couple makes new distinctions and transform them, adapting to what is. The couple unfolds under âless order â fluctuations â more orderâ and confirms the form of process: ârecursion â complexification â next-level-eventsâ. It is shown that next-level-events emerge from self-reflecting sequences of actions. What such view means equates showing (empirically) if such view provides observables, and how such observables are meaningful regarding the analytic process
The Blended Learning Unit, University of Hertfordshire: A Centre for Excellence in Teaching and Learning, Evaluation Report for HEFCE
The University of Hertfordshireâs Blended Learning Unit (BLU) was one of the 74 Centres for Excellence in Teaching and Learning (CETLs) funded by the Higher Education Funding Council for England (HEFCE) between 2005 and 2010. This evaluation report follows HEFCEâs template. The first section provides statistical information about the BLUâs activity. The second section is an evaluative reflection responding to 13 questions. As well as articulating some of our achievements and the challenges we have faced, it also sets out how the BLUâs activity will continue and make a significant contribution to delivery of the University of Hertfordshireâs 2010-2015 strategic plan and its aspirations for a more sustainable future. At the University of Hertfordshire, we view Blended Learning as the use of Information and Communication Technology (ICT) to enhance the learning and learning experience of campus-based students. The University has an excellent learning technology infrastructure that includes its VLE, StudyNet. StudyNet gives students access to a range of tools, resources and support 24/7 from anywhere in the world and its robustness, flexibility and ease of use have been fundamental to the success of the Blended Learning agenda at Hertfordshire. The BLU has comprised a management team, expert teachers seconded from around the University, professional support and a Student Consultant. The secondment staffing model was essential to the success of the BLU. As well as enabling the BLU to become fully staffed within the first five months of the CETL initiative, it has facilitated access to an invaluable spectrum of Blended Learning, research and Change Management expertise to inform pedagogically sound developments and enable change to be embedded across the institution. The BLU used much of its capital funding to reduce barriers to the use of technology by, for example, providing laptop computers for all academic staff in the institution, enhancing classroom technology provision and wirelessly enabling all teaching accommodation. Its recurrent funding has supported development opportunities for its own staff and staff around the institution; supported evaluation activities relating to individual projects and of the BLUâs own impact; and supported a wide range of communication and dissemination activities internally and externally. The BLU has led the embedding a cultural change in relation to Blended Learning at the University of Hertfordshire and its impact will be sustained. The BLU has produced a rich legacy of resources for our own staff and for others in the sector. The Universityâs increased capacity in Blended Learning benefits all our students and provides a learning experience that is expected by the new generation of learners in the 21st century. The BLUâs staffing model and partnership ways of working have directly informed the structure and modus operandi of the Universityâs Learning and Teaching Institute (LTI). Indeed a BLU team will continue to operate within the LTI and help drive and support the implementation of the Universityâs 2010-2015 Strategic plan. The plan includes ambitions in relation to Distance Learning and Flexible learning and BLU will be working to enable greater engagement with students with less or no need to travel to the university. As well as opening new markets within the UK and overseas, even greater flexibility for students will also enable the University to reduce its carbon footprint and provide a multifaceted contribution to our sustainability agenda. We conclude this executive summary with a short paragraph, written by Eeva Leinonen, our former Deputy Vice-Chancellor, which reflects our aspiration to transform Learning and Teaching at the University of Hertfordshire and more widely in the sector. âAs Deputy Vice Chancellor at Hertfordshire I had the privilege to experience closely the excellent work of the Blended Learning Unit, and was very proud of the enormous impact the CETL had not only across the University but also nationally and internationally. However, perhaps true impact is hard to judge at such close range, but now as Vice Principal (Education) at King's College London, I can unequivocally say that Hertfordshire is indeed considered as the leading Blended Learning university in the sector. My new colleagues at King's and other Russell Group Universities frequently seek my views on the 'Hertfordshire Blended Learning' experience and are keen to emulate the successes achieved at an institutional wide scale. The Hertfordshire CETL undoubtedly achieved not only what it set out to achieve, but much more in terms of scale and impact. All those involved in this success can be justifiably proud of their achievements.â Professor Eeva Leinonen, Vice Principal (Education), King's College, Londo
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