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This paper addresses the growing challenges in designing high-performance computing (HPC) workflows that integrate artificial intelligence (AI) components, especially foundation models, which intro…
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This paper addresses the problem of unsupervised continual clustering (UCC), where a neural network must cluster data from a sequence of distinct, unlabeled tasks without storing past data or labels
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This paper addresses the dual challenge of performing deep neural network (DNN) inference on low-end edge devices while simultaneously protecting model confidentiality and enabling verifiable infer…
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This comprehensive survey paper addresses the evolving challenges and methods in video understanding driven by multimodal large language models (MLLMs)
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This paper addresses the challenge of inferring the sign (positive or negative) of social relationships from user interactions in online settings
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Asuka-Bench addresses a critical gap in existing code-generation benchmarks by focusing on iterative, multi-round refinement from underspecified user intents rather than one-shot perfect specificat…
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This paper addresses the challenge of evaluating quality and confidence in Speech Translation (ST) systems by proposing the Speech Translation Error Labelling (STEL) task
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This paper addresses the challenges in constructing benchmarks for evaluating large language models (LLMs) and multimodal large language models (MLLMs), focusing on the problems of labor-intensive …
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This paper addresses the critical limitation in brain-to-image decoding imposed by the scarcity of labeled fMRI data
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This paper addresses a fundamental mismatch in deep learning settings involving test-time feedback (TTF), such as autoregressive language modeling and robot policy learning, where models are traine…
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This paper addresses the underexplored problem of drag grounding in vision-language models (VLMs) for GUI interactions, where the task is to localize both source and target drag coordinates for act…
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Econstellar addresses the significant challenge in computational financial econometrics of enabling accessible, credible, and reproducible empirical research
