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Over the past several years, new machine learning accelerators were being announced and released every month for a variety of applications from speech recognition, video object detection, assisted driving, and many data center applications.…
We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was organized jointly by Amazon and Heidelberg University for the first time at the Second Conference on Machine Translation…
Property-based testing is a mainstay of functional programming, boasting a rich literature, an enthusiastic user community, and an abundance of tools~ -- so many, indeed, that new users may have difficulty choosing. Moreover, any given…
We present DiPerF, a distributed performance testing framework, aimed at simplifying and automating service performance evaluation. DiPerF coordinates a pool of machines that test a target service, collects and aggregates performance…
Machine Translation (MT) has the potential to help people overcome language barriers and is widely used in high-stakes scenarios, such as in hospitals. However, in order to use MT reliably and safely, users need to understand when to trust…
Transformer verification draws increasing attention in machine learning research and industry. It formally verifies the robustness of transformers against adversarial attacks such as exchanging words in a sentence with synonyms. However,…
Testing autonomous vehicles in simulation environments is crucial. Sim-ATAV is an open-source framework developed for experimenting with different test generation techniques in simulation environments for research purposes. This document…
Computer network tends to be subjected to the proliferation of mobile demands and increasingly multifarious, therefore it poses a great challenge to guarantee the quality of network service. By designing the model according to different…
Rapid design space exploration in early design stage is critical to algorithm-architecture co-design for accelerators. In this work, a pre-RTL cycle-accurate accelerator simulator based on SystemC transaction-level modeling (TLM),…
In the design flow of integrated circuits, chip-level verification is an important step that sanity checks the performance is as expected. Power grid verification is one of the most expensive and time-consuming steps of chip-level…
Cloud high quality API (Application Programming Interface) testing is essential for supporting the API economy. Autotest is a random test generator that addresses this need. It reads the API specification and deduces a model used in the…
Neural machine translation (NMT) has set new quality standards in automatic translation, yet its effect on post-editing productivity is still pending thorough investigation. We empirically test how the inclusion of NMT, in addition to…
Novel reinforcement learning algorithms, or improvements on existing ones, are commonly justified by evaluating their performance on benchmark environments and are compared to an ever-changing set of standard algorithms. However, despite…
This study aims to identify the advantages and disadvantages of several mechanisms for service differentiation in mobile terminals of a wireless LAN to establish a more better and more optimal. At the end of the analysis of available…
Automation platforms aim to automate repetitive tasks using workflows, which start with a trigger and then perform a series of actions. However, with many possible actions, the user has to search for the desired action at each step, which…
Serverless computing has grown in popularity in recent years, with an increasing number of applications being built on Functions-as-a-Service (FaaS) platforms. By default, FaaS platforms support retry-based fault tolerance, but this is…
Testing of autonomous systems is extremely important as many of them are both safety-critical and security-critical. The architecture and mechanism of such systems are fundamentally different from traditional control software, which appears…
Business collaboration networks provide collaborative organizations a favorable context for automated business process interoperability. This paper aims to present a novel approach for assessing interoperability of process driven services…
Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual performance. Compared to traditional, non-personalized testing…
Automated driving functions (ADFs) have become increasingly popular in recent years. However, their safety must be assured. Thus, the verification and validation of these functions is still an important open issue in research and…