Customer-obsessed science
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November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models.
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September 2, 20253 min read
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Featured news
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CVPR 2024 Workshop on Fine-Grained Visual Categorization2024Multimodal search has become increasingly important in providing users with a natural and effective way to ex-press their search intentions. Images offer fine-grained details of the desired products, while text allows for easily incorporating search modifications. However, some existing multimodal search systems are unreliable and fail to address simple queries. The problem becomes harder with the large
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2024Assessing the factual consistency of automatically generated texts in relation to source context is crucial for developing reliable natural language generation applications. Recent literature proposes AlignScore which uses a unified alignment model to evaluate factual consistency and substantially outperforms previous methods across many benchmark tasks. In this paper, we take a closer look of datasets
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2024Amazon MemoryDB for Redis is a database service designed for 11 9s of durability with in-memory performance. In this paper, we describe the architecture of MemoryDB and how we leverage open-source Redis, a popular data structure store, to build an enterprise-grade cloud database. MemoryDB offloads durability concerns to a separate low-latency, durable transaction log service, allowing us to scale performance
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2024Object-centric learning (OCL) extracts the representation of objects with slots, offering an exceptional blend of flexibility and interpretability for abstracting low-level perceptual features. A widely adopted method within OCL is slot attention, which utilizes attention mechanisms to iteratively refine slot representations. However, a major drawback of most object-centric models, including slot attention
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2024Recent advancements in machine learning have spotlighted the potential of hyperbolic spaces as they effectively learn hierarchical feature representations. While there has been progress in leveraging hyperbolic spaces in single-modality contexts, its exploration in multimodal settings remains underexplored. A recent work has sought to transpose Euclidean multimodal learning techniques to hyperbolic spaces
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