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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
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This paper addresses the challenge of providing safe and adaptive assistance across diverse tasks in wearable exoskeleton control
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This study investigates the evolution of bilateral and multilateral international research collaboration for nine EU-14 member states over the period 2010 to 2024, spanning six scientific disciplin…
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This paper addresses the challenge of vessel trajectory prediction from irregularly sampled and partially missing AIS maritime data, emphasizing the importance of calibrated uncertainty estimates f…
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This paper addresses the problem of dataset condensation specifically tailored for diffusion model training
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This paper addresses the challenge of generating realistic, coherent, and simulation-ready whole-home indoor scenes from high-level user prompts
