Generative Conversational Agents- The State-of-the-Art and the Future of Intelligent Conversational Systems

Intelligent conversational agents that generate responses from scratch are rapidly gaining in popularity. Sequence-to-sequence deep learning models are particularly well-suited for generating a textual response from a query. In this paper, I describe various generative models that are capable of having open-domain conversations. Toward the end, I present a null result I obtained in an attempt to train a chatbot from a small dataset and propose the use of a deep memory based machine translation model for training chatbots on small datasets

Application of Quantum Natural Language Processing for Language Translation

In this paper, we develop compositional vector-based semantics of positive transitive sentences using quantum natural language processing (Q-NLP) to compare the parametrized quantum circuits of two synonymous simple sentences in English and Persian. We propose a protocol based on quantum long short-term memory (Q-LSTM) for Q-NLP to perform various tasks in general but specifically for translating a sentence from English to Persian. Then, we generalize our method to use quantum circuits of sentences as an input for the Q-LSTM cell. This enables us to translate sentences in different languages. Our work paves the way toward representing quantum neural machine translation, which may demonstrate quadratic speedup and converge faster or reaches a better accuracy over classical methods

Remembering Poland: The Ethics of Cultural Histories

Art Spiegelman\u27s Maus, Cynthia Ozick\u27s The Shawl, and Eva Hoffman\u27s Lost in Translation and Exit into History are recent American texts that draw upon cultural histories of Poland to launch their narratives. Each text confronts and reconstructs fragments of twentieth-century Poland at the interactive sites of collective culture and personal memory. By focusing on the contested relationship between Poles and Jews before, during, and after World War II, these texts dredge up the ghosts of centuries-long ethnic animosities. In the post-Cold War era, wherein Eastern Europe struggles to redefine itself, such texts have a formative influence in re-mapping the future of national identities

"Consciousness". Selected Bibliography 1970 - 2001

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience (Metzinger 1995a, b). From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001

A Feeling for History? Bakhtin and `The Problem of Great Time'

‘Great time’ has usually been seen as a ‘late term’ of Bakhtin’s. However, although it occurs most frequently in works written in the 1960s and 1970s, there is one known instance of its use in the 1940s. This confirms the close association between the notion and Bakhtin’s dominant concerns of the 1930s and 1940s, in particular the ‘becoming’ that he associates with the novel in general and the Bildungsroman in particular. ‘Great time’ thus needs to be examined in the context of the connections between his thought and Hegelian antecedents, as well as his of his approach to time in terms of other models, both philosophical and anthropological

The Method of Teaching New Testament Greek

Based on teaching experience the author proposes an approach to teaching New Testament Greek which has resulted in greater use of the langauge and less fear of its study

Technology for large-scale translation of clinical practice guidelines : a pilot study of the performance of a hybrid human and computer-assisted approach

Background: The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, was initiated in 2011 to optimize quality of care by promoting evidence-based decision-making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL Multiterm termbases) from medical termbases and support from online machine translation. This has resulted in a validated translation memory which is now in use for the translation of new and updated guidelines. Objective: The objective of this study was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator. Methods: We conducted a pilot trial in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (a) by certificated junior translators without medical specialization using the hybrid method (b) by an experienced medical translator without this support and (c) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The Human Translation Edit Rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of translation acceptability and adequacy. Results: The average number of words per guideline was 1,195 and the mean total translation time was 100.2 min/1,000 words. No meaningful differences were found in the translation speed for new guidelines. The translation of updated guidelines was 59 min/1,000 words faster (95% CI 2-115; P=.044) in the computer-aided group. Revisions due to terminology accounted for one third of the overall revisions by the medical proofreader. Conclusions: Use of the hybrid human and computer-aided translation by a non-expert translator makes the translation of updates of clinical practice guidelines faster and cheaper because of the benefits of translation memory. For the translation of new guidelines there was no apparent benefit in comparison with the efficiency of translation unsupported by translation memory (whether by an expert or non-expert translator

A Hierarchical Neural Autoencoder for Paragraphs and Documents

Natural language generation of coherent long texts like paragraphs or longer documents is a challenging problem for recurrent networks models. In this paper, we explore an important step toward this generation task: training an LSTM (Long-short term memory) auto-encoder to preserve and reconstruct multi-sentence paragraphs. We introduce an LSTM model that hierarchically builds an embedding for a paragraph from embeddings for sentences and words, then decodes this embedding to reconstruct the original paragraph. We evaluate the reconstructed paragraph using standard metrics like ROUGE and Entity Grid, showing that neural models are able to encode texts in a way that preserve syntactic, semantic, and discourse coherence. While only a first step toward generating coherent text units from neural models, our work has the potential to significantly impact natural language generation and summarization\footnote{Code for the three models described in this paper can be found at www.stanford.edu/~jiweil/