Prior studies on text-to-text generation typically assume that the model could figure out what to attend to in the input and what to include in the output via seq2seq learning, with only the parallel training data and no additional guidance. However,
it remains unclear whether current models can preserve important concepts in the source input, as seq2seq learning does not have explicit focus on the concepts and commonly used evaluation metrics also treat them equally important as other tokens. In this paper, we present a systematic analysis that studies whether current seq2seq models, especially pre-trained language models, are good enough for preserving important input concepts and to what extent explicitly guiding generation with the concepts as lexical constraints is beneficial. We answer the above questions by conducting extensive analytical experiments on four representative text-to-text generation tasks. Based on the observations, we then propose a simple yet effective framework to automatically extract, denoise, and enforce important input concepts as lexical constraints. This new method performs comparably or better than its unconstrained counterpart on automatic metrics, demonstrates higher coverage for concept preservation, and receives better ratings in the human evaluation. Our code is available at https://github.com/morningmoni/EDE.
We investigate ways to compose complex concepts in texts from primitive ones while grounding them in images. We propose Concept and Relation Graph (CRG), which builds on top of constituency analysis and consists of recursively combined concepts with
predicate functions. Meanwhile, we propose a concept composition neural network called Composer to leverage the CRG for visually grounded concept learning. Specifically, we learn the grounding of both primitive and all composed concepts by aligning them to images and show that learning to compose leads to more robust grounding results, measured in text-to-image matching accuracy. Notably, our model can model grounded concepts forming at both the finer-grained sentence level and the coarser-grained intermediate level (or word-level). Composer leads to pronounced improvement in matching accuracy when the evaluation data has significant compound divergence from the training data.
This paper focuses on paraphrase generation,which is a widely studied natural language generation task in NLP. With the development of neural models, paraphrase generation research has exhibited a gradual shift to neural methods in the recent years.
This has provided architectures for contextualized representation of an input text and generating fluent, diverseand human-like paraphrases. This paper surveys various approaches to paraphrase generation with a main focus on neural methods.
Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module. Owing to numerous surface variants of biomedical concepts, BCN still remains challenging and unsolved. In this paper, we exploit biomedical c
oncept hypernyms to facilitate BCN. We propose Biomedical Concept Normalizer with Hypernyms (BCNH), a novel framework that adopts list-wise training to make use of both hypernyms and synonyms, and also employs norm constraint on the representation of hypernym-hyponym entity pairs. The experimental results show that BCNH outperforms the previous state-of-the-art model on the NCBI dataset.
Humans are remarkably flexible when understanding new sentences that include combinations of concepts they have never encountered before. Recent work has shown that while deep networks can mimic some human language abilities when presented with novel
sentences, systematic variation uncovers the limitations in the language-understanding abilities of networks. We demonstrate that these limitations can be overcome by addressing the generalization challenges in the gSCAN dataset, which explicitly measures how well an agent is able to interpret novel linguistic commands grounded in vision, e.g., novel pairings of adjectives and nouns. The key principle we employ is compositionality: that the compositional structure of networks should reflect the compositional structure of the problem domain they address, while allowing other parameters to be learned end-to-end. We build a general-purpose mechanism that enables agents to generalize their language understanding to compositional domains. Crucially, our network has the same state-of-the-art performance as prior work while generalizing its knowledge when prior work does not. Our network also provides a level of interpretability that enables users to inspect what each part of networks learns. Robust grounded language understanding without dramatic failures and without corner cases is critical to building safe and fair robots; we demonstrate the significant role that compositionality can play in achieving that goal.
Biomaterials are synthetic or natural materials used for constructing artificial organs, fabricating prostheses, or replacing tissues. The last century saw the development of thousands of novel biomaterials and, as a result, an exponential increase i
n scientific publications in the field. Large-scale analysis of biomaterials and their performance could enable data-driven material selection and implant design. However, such analysis requires identification and organization of concepts, such as materials and structures, from published texts. To facilitate future information extraction and the application of machine-learning techniques, we developed a semantic annotator specifically tailored for the biomaterials literature. The Biomaterials Annotator has been implemented following a modular organization using software containers for the different components and orchestrated using Nextflow as workflow manager. Natural language processing (NLP) components are mainly developed in Java. This set-up has allowed named entity recognition of seventeen classes relevant to the biomaterials domain. Here we detail the development, evaluation and performance of the system, as well as the release of the first collection of annotated biomaterials abstracts. We make both the corpus and system available to the community to promote future efforts in the field and contribute towards its sustainability.
In this research I studied structural concepts , and how to move into the Arabic
cultural field. I defined these concepts, and the most important people who founded it and
contributed to its construction as a structural approach . Then I traced the
ways that
brought it to the modern Arabic criticism .And the role of competency in the process of
vulnerability and influence. Perhaps the practical steps I have taken has made the structural
approach take its obvious features in our Arabic criticism. This research is presented in
detail by the structural critic Kamal Abu Dib , through his structural applications. And
because it is impossible to take note of all structural aspects that resembled the archipelago
to look up from the top, I tried to study structuralism as a way of thinking and literary
criticism. In particular ,structuralism seeks to discover the relationship between the literary
system ( the text ) and the culture , that the text part of it.
This research has answer the question: how can structure reinforce
architectural design concepts in order to enrich architecture? After
acknowledging the relevance of design concepts in architecture,
recurring concepts in contemporary architecture were identified. The
most prevalent concepts found can be summarized as pairs of
opposing concepts: order-chaos, grounded-floating.
This paper deals with the transition, which is noted in the concept of the right to selfdetermination
under the influence of the increasing interest in the issues of
democracy and human rights and the accompanying growing globalization of
problems
, And notably those arising from the relationship of ethnic or religious
minorities with the governments of its mother, which is now rising in many voices
calling to go towards the prevention of such minorities the right to secession and
legitimize public international law on such a separation under the title of the right to
self-determination , This prompted some scholars and researchers for a shift in the
concept of this right from the fact that he want international mechanism to achieve
the independence of States under the yoke of colonialism and to ensure undertaken
to full sovereignty over its national territory to a means of settling internal conflicts
waged by some minorities with the governments of its countries Which requires to
shed light on this transformation and its compatibility statement with the concept
and content of the right to self-determination, with the study of the contemporary
situation of those cases, namely the secession of southern Sudan to give as much
vitality to the research and its results
في هذا البحث المتواضع أردت أن أقف عند سؤال الأخلاق في الفلسفة الغربية منذ نهضتها الأولى في العهد اليوناني إلى العصر الحديث، و عصر الأنوار؛ لإلقاء الضوء على مكونات العقلية الغربية –و بالأخص السياسية منها – في النظرة إلى الآخر، لأن الموقف الفلسفي في ال
غالب هو الذي يشكل الموقف السياسي، فضلاً عن الموقف الديني، و لا شك أننا ندرك أن الدين هو الرافد الأول للفلسفة، فهما يتعاضدان في تشكيل مواقف الأمم، و خصوصاً المواقف الكبرى و المصيرية، و لكي تتضح الصورة جلية فقد لجأت إلى المقارنة المختصرة بين الفلسفة الغربية و الرؤية الإسلامية، فكان منهج البحث منهجاً تاريخياً استقرائياً مقارناً.
