Methods to generate text from structured data have advanced significantly in recent years, primarily due to fine-tuning of pre-trained language models on large datasets. However, such models can fail to produce output faithful to the input data, particularly on out-of-domain data. Sufficient annotated data is often not available for specific domains, leading us to seek an unsupervised approach to improve the faithfulness of output text. Since the problem is fundamentally one of consistency between the representations of the structured data and text, we evaluate the effectiveness of cycle training in this work. Cycle training uses two models which are inverses of each other: one that generates text from structured data, and one which generates the structured data from natural language text. We show that cycle training, when initialized with a small amount of supervised data (100 samples in our case), achieves nearly the same performance as fully supervised approaches for the data-to-text generation task on the WebNLG, E2E, WTQ, and WSQL datasets. We perform extensive empirical analysis with automated evaluation metrics and a newly designed human evaluation schema to reveal different cycle training strategies' effectiveness of reducing various types of generation errors. Our code is publicly available at https://github.com/Edillower/CycleNLG.

JANUS translates continuously spoken English and German into German, English, and Japanese. JANUS cur(cid:173) rently achieves 87% translation fidelity from English speech and 97% from German speech. We present the JANUS system along with com(cid:173) parative evaluations of its interchangeable processing components, with special emphasis on the connectionist modules.

TeamViewer is a leading global technology company that provides a cutting-edge platform to remotely access, control and support devices of any kind. Our software solutions empower our users and customers to bridge distances and digitalize their processes through seamless connectivity. Our team is committed to quality and passionately leading the way in the fields of Augmented Reality, Internet of Things and Artificial Intelligence. With over 1.400 employees from more than 80 nationalities in 20 locations worldwide, we are one global family. We believe that bringing together people from different backgrounds and experiences leads to better, more innovative solutions.

The reality of self-driving cars and autonomous public transport is almost upon us. In Karlsruhe, three autonomous buses have been running since April. The buses don't run specific routes, rather, they can be ordered to certain places. Back in April, the city of Karlsruhe welcomed Vera, Ella and Anna to its streets. These are the names of three autonomous e-buses, which are part of a project funded by the Ministry for Transport.

Karlsruhe, August 29, 2019 – At the SEMANTiCS conference in Karlsruhe from 9 to 12 September, representatives from industry and science will discuss the use of semantic technologies and artificial intelligence. FIZ Karlsruhe is a co-organizer, and with good reason: the digital change has reached and affected research data, methods and processes. Efficient information infrastructures have a key role to play in mastering the new challenges. FIZ Karlsruhe will present its spectrum as a Leibniz Institute for Information Infrastructure in various roundtable discussions, presentations and with its own stand. SEMANTiCS is one of the leading conferences in the field of semantic technologies and artificial intelligence. FIZ Karlsruhe, together with the Karlsruhe Institute of Technology (KIT), has succeeded in bringing this renowned international event to Karlsruhe for its 15th anniversary.

Dear Editor: ... May I also take this opportunity to praise the staff of the AI Magazine for a most informative and professional journal, and one which I find increasingly important for acquainting me with the latest progress in American research. I look forward to the continuing success of the Association in all its activities. Dear Sir, Yours sincerely, Marten E. Bennett Gzllingham, Kent, UK I would like to comment on something disturbing that appeared to be revealed at the recent I J C AI conference at Karlsruhe. The background to it is the "Marietta affair." At the industrial exhibition associated with the conference a Germany company, Marietta, was due to mount an exhibit.

Submitted Papers chairman will call for a third opinion, and failing that, I will decide. You should know the outcome soon after April 1st. I want to sharpen the distinction between the "long" and'short" to remove some of the ambiguity about their role. Long papers are for finished, high quality work. In fact, IJCAIs are the premier forum for such work.

What is the Semantic Web? "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" Machines should not just be able to display data, but rather be able to use it for automation, integration and reuse across various applications. The European Commission is funding numerous projects related to Ontologies and the Semantic Web; even more will be funded in its recently launched Sixth Framework Research Programme. The worldwide Semantic Web community is growing rather fast and forces are being joined with other technology developments such as Web Services or multimedia. Last, but not least, vendors are already offering mature products and solutions based on semantic technologies. Thus, the Semantic Web is currently moving from being a vision to becoming reality.

Knowledge portals provide views onto domain-specific information on the World Wide Web, thus helping their users find relevant, domain-specific information. The construction of intelligent access and the contribution of information to knowledge portals, however, remained an ad hoc task, requiring extensive manual editing and maintenance by the knowledge portal providers. To diminish these efforts, we use ontologies as a conceptual backbone for providing, accessing, and structuring information in a comprehensive approach for building and maintaining knowledge portals. We present one research study and one commercial case study that show how our approach, called seal (semantic portal), is used in practice.

When I took on the job of programme chairman of IJCAI-83 the trustees presented me with a list of problems with the way IJCAI programmes had traditionally been organized. Some of these problems had been raised by previous programme chairmen, some by attendees and some been subsequently been raised by me. I have tried to organise the IJCAI-83 programme to solve these problems -or at least some of them, I have been unable to devise a scheme which simultaneously solves all the problems. (I leave this as an exercise for the reader.) My plans converged after consultation with many people in the AI community, including the IJCAI-83 conference committee, and they have that committee's approval. Inevitably this means that IJCAI-83 will be a little different from here-to -fore, and in order for my changes to be also solutions, it is necessary for you, the paying customer, to be aware of these differences and to take advantage of them. The aim of this article is to raise you awareness.