Found 10 document(s)
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AI coding agents routinely clone repositories, install packages, and read source code obtained from the Web, so publicly hosted code becomes part of the context that shapes the code they write. We show that this Web-born...
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Foundation models provide powerful representations for unstructured data, such as text and images, and parameter-efficient fine-tuning (PEFT) makes their adaptation to downstream tasks increasingly practical. For neural ...
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ClinVerse: A Realistic Multi-Agent Diagnostic Environment for Training and Evaluating Medical AgentsDisease diagnosis is a key application of large language model (LLM) agents in healthcare. However, existing medical agents are primarily trained and evaluated with static question-answering data, providing limited oppor...
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Diffusion-based real-world image super-resolution suffers from limited reconstruction fidelity due to information loss in VAE-based latent representations. Recently, pixel-space diffusion models offer a promising high-fa...
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Adapting a pre-trained machine-learning interatomic potential for non-equilibrium defect dynamics and plasticity requires improving defect accuracy without degrading the near-equilibrium elastic and vibrational response....
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Developers rely more and more on so-called End To End (E2E) tests to test the web applications they develop and to check that they have no bug from an end-user point of view. An E2E test simulates the actions performed b...
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This paper considers the problem of continuous-time model identification with arbitrary time-delay from irregularly sampled data. The proposed method estimates the plant and the time-delay in a separable way, when estima...
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L'objet de cette communication est de présenter, de manière succincte, un prototype du logiciel FER/Mesh-un logiciel de génération automatique de maillages pour le calcul par éléments finis. L'algorithme du maillage est ...
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In real scenes, dynamic background and moving cast shadow always make accurate moving object detection difficult. In this paper, a probabilistic framework for moving object segmentation in dynamic scenes is proposed. Und...