CEA won the EvalLLM 2024 challenge, organized by the French Ministerial Agency for AI and Defense (AMIAD) in May 2024.
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CEA-List’s probabilistic deep learning tools can be used to quantitatively measure prediction reliability.
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CEA-List researchers developed PyRAT, a formal verification tool for neural networks, to respond to growing demand for more reliable AI-based systems.
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The principle of object discovery is the location of objects without the need for human-annotated data. And, unlike conventional object detection systems, object discovery can handle unknown object classes.
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CEA-List’s smart robotics demonstrator highlights generative AI’s potential as an enabler of robotic tasks whose instructions are given in natural language.
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CEA-List created an algorithm that enables automated news content analysis.
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The European project CIRPASS, coordinated by CEA-List, proposed a blueprint for the connected information system that will support the circular economy.
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CEA-List conducted a study to clarify associated terms and definitions and produce a methodological framework to characterizing eco-innovation in a technological research project
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At the request of cybersecurity firm Vade, CEA-List engineered a first line of defense to new cyberattack vectors: AI-generated text detection.
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Fault injection attacks threaten the security of digital systems. CEA-List and Graz Technical University (Austria) developed a new pre-silicon analysis method that led to the world’s first demonstration of the robustness of a processor and its boot code against these attacks.
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