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  1. WikiFactDiff is a dataset designed as a resource to perform atomic factual knowledge updates on language models, with the goal of aligning them with current knowledge. It describes the evolution of factual knowledge between two dates, named T_old and T_new,​ in the form of semantic triples. To enable the possibility of evaluating knowledge algorithms (such […]

  2. Machine learning, in its various tasks from fitting to inference, can be highly energy intensive and raises growing environmental concerns. This situation inspired different initiatives fostering a more frugal, greener AI. Beyond the implementation of good practices, it appears pivotal for researchers and data engineers to gather an empiric knowledge of energy consumption per task, […]

  3. Marine Detect is an innovative project that leverages Deep Learning technology to advance the detection and identification of marine species. These models were developed in the context of the Let’s Revive project in partnership with Tēnaka. Tēnaka emphasizes impact measurement through Tēnaka Science, a platform sharing monthly coral ecosystems data. To automate data collection, Orange […]

  4. Speech processing models are computationally expensive, generating environmental concerns because of their high energy consumption. ESSL (Efficient Self-Supervised Learning) addresses this issue, enabling pretraining with a single GPU for only 28 hours. The reduction in computational costs represents up to two orders of magnitude improvement against existing speech models. Its source code is available on […]

  5. Explore the functionality of Orange Design System Charts, a dynamic JavaScript data visualization library built on top of Apache ECharts. This library facilitates the seamless integration of various Orange-branded chart types into websites, ranging from straightforward line charts to more complex pie charts, bar charts, and beyond. With a focus on practicality for Orange developers […]

  6. Generative models for dialogue state tracking using RDF State-of-the-art models assume a dialogue state representation based on concepts (slots) and their associated values. For example the system, at some point in the conversation, may believe the user wants the “price” to be “cheap”. However, real world applications naturally show dependencies between concepts: price and location […]

  7. An abstraction and access control layer for containers on RIOT OS TinyContainer allows to deploy an IoT logic adapted to a context (personalized user experience or deployment of an intelligence model) while controlling access to the exposed IoT resources. TinyContainer was presented in the RIOT Summit in September 2023. In the presentation, we described the […]

  8. UUV is a solution to facilitate the writing and execution of ento-end (E2E) tests understandable by any human. It’s a coherent ecosystem based on tools that are references in their field: Axe-core, Testing Library, Cucumber, Cypress and Playwright. If used correctly, it integrates accessibility from the development stage, and can be used to establish living […]