Toward an architecture for quantum programming

It is becoming increasingly clear that, if a useful device for quantum computation will ever be built, it will be embodied by a classical computing machine with control over a truly quantum subsystem, this apparatus performing a mixture of classical and quantum computation. This paper investigates a possible approach to the problem of programming such machines: a template high level quantum language is presented which complements a generic general purpose classical language with a set of quantum primitives. The underlying scheme involves a run-time environment which calculates the byte-code for the quantum operations and pipes it to a quantum device controller or to a simulator. This language can compactly express existing quantum algorithms and reduce them to sequences of elementary operations; it also easily lends itself to automatic, hardware independent, circuit simplification. A publicly available preliminary implementation of the proposed ideas has been realized using the C++ language.Comment: 23 pages, 5 figures, A4paper. Final version accepted by EJPD ("swap" replaced by "invert" for Qops). Preliminary implementation available at: http://sra.itc.it/people/serafini/quantum-computing/qlang.htm

Language-based multimedia information retrieval

This paper describes various methods and approaches for language-based multimedia information retrieval, which have been developed in the projects POP-EYE and OLIVE and which will be developed further in the MUMIS project. All of these project aim at supporting automated indexing of video material by use of human language technologies. Thus, in contrast to image or sound-based retrieval methods, where both the query language and the indexing methods build on non-linguistic data, these methods attempt to exploit advanced text retrieval technologies for the retrieval of non-textual material. While POP-EYE was building on subtitles or captions as the prime language key for disclosing video fragments, OLIVE is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which then serve as the basis for text-based retrieval functionality

Neural Machine Translation into Language Varieties

Both research and commercial machine translation have so far neglected the importance of properly handling the spelling, lexical and grammar divergences occurring among language varieties. Notable cases are standard national varieties such as Brazilian and European Portuguese, and Canadian and European French, which popular online machine translation services are not keeping distinct. We show that an evident side effect of modeling such varieties as unique classes is the generation of inconsistent translations. In this work, we investigate the problem of training neural machine translation from English to specific pairs of language varieties, assuming both labeled and unlabeled parallel texts, and low-resource conditions. We report experiments from English to two pairs of dialects, EuropeanBrazilian Portuguese and European-Canadian French, and two pairs of standardized varieties, Croatian-Serbian and Indonesian-Malay. We show significant BLEU score improvements over baseline systems when translation into similar languages is learned as a multilingual task with shared representations.Comment: Published at EMNLP 2018: third conference on machine translation (WMT 2018

Frame Shift/warp Compensation for the ARID Robot System

The Automatic Radiator Inspection Device (ARID) is a system aimed at automating the tedious task of inspecting orbiter radiator panels. The ARID must have the ability to aim a camera accurately at the desired inspection points, which are in the order of 13,000. The ideal inspection points are known; however, the panel may be relocated due to inaccurate parking and warpage. A method of determining the mathematical description of a translated as well as a warped surface by accurate measurement of only a few points on this surface is developed here. The method uses a linear warp model whose effect is superimposed on the rigid body translation. Due to the angles involved, small angle approximations are possible, which greatly reduces the computational complexity. Given an accurate linear warp model, all the desired translation and warp parameters can be obtained by knowledge of the ideal locations of four fiducial points and the corresponding measurements of these points on the actual radiator surface. The method uses three of the fiducials to define a plane and the fourth to define the warp. Given this information, it is possible to determine a transformation that will enable the ARID system to translate any desired inspection point on the ideal surface to its corresponding value on the actual surface

Designing a CPU model: from a pseudo-formal document to fast code

For validating low level embedded software, engineers use simulators that take the real binary as input. Like the real hardware, these full-system simulators are organized as a set of components. The main component is the CPU simulator (ISS), because it is the usual bottleneck for the simulation speed, and its development is a long and repetitive task. Previous work showed that an ISS can be generated from an Architecture Description Language (ADL). In the work reported in this paper, we generate a CPU simulator directly from the pseudo-formal descriptions of the reference manual. For each instruction, we extract the information describing its behavior, its binary encoding, and its assembly syntax. Next, after automatically applying many optimizations on the extracted information, we generate a SystemC/TLM ISS. We also generate tests for the decoder and a formal specification in Coq. Experiments show that the generated ISS is as fast and stable as our previous hand-written ISS.Comment: 3rd Workshop on: Rapid Simulation and Performance Evaluation: Methods and Tools (2011

C to O-O Translation: Beyond the Easy Stuff

Can we reuse some of the huge code-base developed in C to take advantage of modern programming language features such as type safety, object-orientation, and contracts? This paper presents a source-to-source translation of C code into Eiffel, a modern object-oriented programming language, and the supporting tool C2Eif. The translation is completely automatic and supports the entire C language (ANSI, as well as many GNU C Compiler extensions, through CIL) as used in practice, including its usage of native system libraries and inlined assembly code. Our experiments show that C2Eif can handle C applications and libraries of significant size (such as vim and libgsl), as well as challenging benchmarks such as the GCC torture tests. The produced Eiffel code is functionally equivalent to the original C code, and takes advantage of some of Eiffel's object-oriented features to produce safe and easy-to-debug translations

Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses

Automatically evaluating the quality of dialogue responses for unstructured domains is a challenging problem. Unfortunately, existing automatic evaluation metrics are biased and correlate very poorly with human judgements of response quality. Yet having an accurate automatic evaluation procedure is crucial for dialogue research, as it allows rapid prototyping and testing of new models with fewer expensive human evaluations. In response to this challenge, we formulate automatic dialogue evaluation as a learning problem. We present an evaluation model (ADEM) that learns to predict human-like scores to input responses, using a new dataset of human response scores. We show that the ADEM model's predictions correlate significantly, and at a level much higher than word-overlap metrics such as BLEU, with human judgements at both the utterance and system-level. We also show that ADEM can generalize to evaluating dialogue models unseen during training, an important step for automatic dialogue evaluation.Comment: ACL 201

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems