Articles
Total Articles: 38870
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14151
AbstractWe report on our attempts to reproduce the work described in Vajjala & Rama 2018, ‘Experiments with universal CEFR classification’, as part of REPROLANG 2020: this involves featured-based and neural approaches to essay scoring in Czech, German and Italian. Our results are broadly in line with those from the original …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14152
AbstractAs in many experimental sciences, reproducibility of experiments has gained ever more attention in the NLP community. This paper presents our reproduction efforts of an earlier study of automatic essay scoring (AES) for determining the proficiency of second language learners in a multilingual setting. We present three sets of experiments …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14153
Abstracthis study aims to reproduce the research of Vajjala and Rama (2018) which showed that it is possible to predict the quality of a text written by learners of a given language by means of a model built on the basis of texts written by learners of another language. These …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14154
AbstractThis work presents a replication study of Exploring Neural Text Simplification Models (Nisioi et al., 2017). We were able to successfully replicate and extend the methods presented in the original paper. Alongside the replication results, we present our improvements dubbed CombiNMT. By using an updated implementation of OpenNMT, and incorporating …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14155
AbstractIn order to achieve interoperability of information in the context of the Semantic Web, it is necessary to find effective ways to align different ontologies. As the number of ontologies grows for a given domain, and as overlap between ontologies grows proportionally, it is becoming more and more crucial to …...
ULMFiT replication
14156nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14156
AbstractAuthors: Mohamed Abdellatif and Ahmed Elgammal Gitlab URL: https://gitlab.com/abdollatif/lrec_app Commit hash: 3f20b2ddb96d8c865e5f56f5566edf371214785f Tag name: Splits2 Dataset file md5: 5aee3dac5e48d1ac3d279083212734c9 Dataset URL: https://drive.google.com/file/d/1cv5HuQhgFVizupFI40dzreemS2gMM498/view?usp=sharing...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14157
AbstractWithin the natural language processing (NLP) community, shared tasks play an important role. They define a common goal and allowthe the comparison of different methods on the same data. SemEval-2018 Task 7 involves the identification and classification of relationsin abstracts from computational linguistics (CL) publications. In this paper we describe …...
Reproducing a Morphosyntactic Tagger with a Meta-BiLSTM Model over Context Sensitive Token Encodings
14158nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14158
AbstractReproducibility is generally regarded as being a requirement for any form of experimental science. Even so, reproduction of research results is only recently beginning to be practiced and acknowledged. In the context of the REPROLANG 2020 shared task, we contribute to this trend by reproducing the work reported on by …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14159
AbstractIn this work, we study the unsupervised cross-lingual word embeddings mapping method presented by Artetxe et al. (2018). First, wesuccessfully reproduced the experiments performed in the original work, finding only minor differences. Furthermore, we verified themethod’s robustness on different embedding representations and new language pairs, particularly these involving Slavic languages …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14160
AbstractWe evaluate the performance of various Transformer language models, when pre-trained and fine-tuned on different combinations of open-domain, biomedical, and clinical corpora on two clinical question answering (QA) datasets (CliCR and emrQA). We perform our evaluations on the task of machine reading comprehension, which involves training the model to answer …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14161
AbstractIn this paper, we reproduce the experiments of Artetxe et al. (2018b) regarding the robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings. We show that the reproduction of their method is indeed feasible with some minor assumptions. We further investigate the robustness of their model by introducing …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14162
Abstractn this paper, we introduce a new type of shared task — which is collaborative rather than competitive — designed to support and fosterthe reproduction of research results. We also describe the first event running such a novel challenge, present the results obtained, discussthe lessons learned and ponder on future …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14163
AbstractWe present ScholarlyRead, span-of-word-based scholarly articles’ Reading Comprehension (RC) dataset with approximately 10K manually checked passage-question-answer instances. ScholarlyRead was constructed in semi-automatic way. We consider the articles from two popular journals of a reputed publishing house. Firstly, we generate questions from these articles in an automatic way. Generated questions are …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14164
AbstractMachine Reading received recently a lot of attention thanks to both the availability of very large corpora such as SQuAD or MS MARCO containing triplets (document, question, answer), and the introduction of Transformer Language Models such as BERT which obtain excellent results, even matching human performance according to the SQuAD …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14165
AbstractMotivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to collect a native French Question Answering Dataset. Furthermore, we describe and publicly release the annotation tool developed for our collection effort, along with …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14166
AbstractWe present a voice-based conversational agent which combines the robustness of chatbots and the utility of question answering (QA) systems. Indeed, while data-driven chatbots are typically user-friendly but not goal-oriented, QA systems tend to perform poorly at chitchat. The proposed chatbot relies on a controller which performs dialogue act classification …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14167
AbstractExplainable question answering for complex questions often requires combining large numbers of facts to answer a question while providing a human-readable explanation for the answer, a process known as multi-hop inference. Standardized science questions require combining an average of 6 facts, and as many as 16 facts, in order to …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14168
AbstractVisual Question Answering (VQA) has been widely explored as a computer vision problem, however enhancing VQA systems with linguistic information is necessary for tackling the complexity of the task. The language understanding part can play a major role especially for questions asking about events or actions expressed via verbs. We …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14169
AbstractDespite the number of currently available datasets on video-question answering, there still remains a need for a dataset involving multi-step and non-factoid answers. Moreover, relying on video transcripts remains an under-explored topic. To adequately address this, we propose a new question answering task on instructional videos, because of their verbose …...
nan
Publication: TIPSTER (2020)
DOI: nan
Paper ID: 14170
AbstractWe present AIA-BDE, a corpus of 380 domain-oriented FAQs in Portuguese and their variations, i.e., paraphrases or entailed questions, created manually, by humans, or automatically, with Google Translate. Its aims to be used as a benchmark for FAQ retrieval and automatic question-answering, but may be useful in other contexts, such …...