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In the era of artificial intelligence, the diversity of data modalities and annotation formats often renders data unusable directly, requiring understanding and format conversion before it can be used by researchers or developers with…
Despite tremendous progress in natural language processing using deep learning techniques in recent years, sign language production and comprehension has advanced very little. One critical barrier is the lack of largescale datasets…
Common data types like dates, addresses, phone numbers and tables can have multiple textual representations, and many heavily-used languages, such as SQL, come in several dialects. These variations can cause data to be misinterpreted,…
We propose a Vision-Language Simulation Model (VLSM) that unifies visual and textual understanding to synthesize executable FlexScript from layout sketches and natural-language prompts, enabling cross-modal reasoning for industrial…
Today's database is associated with interoperability between different domains and applications. This consequently results in the importance of data portability in database. XML format fits the requirements and it has been increasingly used…
Like spoken languages, a single sign language expression could correspond to multiple valid textual interpretations. Hence, learning a rigid one-to-one mapping for sign language translation (SLT) models might be inadequate, particularly in…
Event-driven programming is used in many fields of modern Computer Science. In event-driven programming languages user interacts with a program by triggering the events. We propose a new approach that we denote command-event driven…
The file system provides the mechanism for online storage and access to file contents, including data and programs. This paper covers the high-level details of file systems, as well as related topics such as the disk cache, the file system…
When components of a system exchange data, they need to serialise the data so that it can be sent over the network. Then, the recipient has to deserialise the data in order to be able to process it. These steps take time and have an impact…
Product Data Management (PDM) aims to provide 'Systems' contributing in industries by electronically maintaining organizational data, improving data repository system, facilitating with easy access to CAD and providing additional…
Semantic Textual Similarity (STS) is a crucial component of many Natural Language Processing (NLP) applications. However, existing approaches typically reduce semantic nuances to a single score, limiting interpretability. To address this,…
Mining data streams is a challenge per se. It must be ready to deal with an enormous amount of data and with problems not present in batch machine learning, such as concept drift. Therefore, applying a batch-designed technique, such as…
We present a unified programming model for heterogeneous computing systems. Such systems integrate multiple computing accelerators and memory units to deliver higher performance than CPU-centric systems. Although heterogeneous systems have…
Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, for executing the resulting automated workflows, and for recording the provenance of data products resulting…
Multivariate Time Series Forecasting plays a key role in many applications. Recent works have explored using Large Language Models for MTSF to take advantage of their reasoning abilities. However, many methods treat LLMs as end-to-end…
Mathematical programming is a branch of applied mathematics and has recently been used to derive new decoding approaches, challenging established but often heuristic algorithms based on iterative message passing. Concepts from mathematical…
Since the early days of the Web, web application developers have aspired to develop much of their applications declaratively. However, one aspect of the application, namely its business-logic is constantly left imperative. In this work we…
A classical problem in Software Engineering is how to certify that every system requirement is correctly implemented by source code. This problem, albeit well studied, can still be considered an open one, given the problems faced by…
Building deployment-ready LLM agents requires complex orchestration of tools, data sources, and control flow logic, yet existing systems tightly couple agent logic to specific programming languages and deployment models. We present a…
Due to the long runtime of Data Science (DS) pipelines, even small programming mistakes can be very costly, if they are not detected statically. However, even basic static type checking of DS pipelines is difficult because most are written…