MammoClean: Toward Reproducible and Bias-Aware AI in Mammography through Dataset Harmonization
arxiv.org·3d
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Collaborative Attention and Consistent-Guided Fusion of MRI and PET for Alzheimer's Disease Diagnosis
arxiv.org·3d
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The Benefits of Data Storytelling in Accessible Teaching
arxiv.org·1d
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Studying the Effect of Explicit Interaction Representations on Learning Scene-level Distributions of Human Trajectories
arxiv.org·1d
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KoTaP: A Panel Dataset for Corporate Tax Avoidance, Performance, and Governance in Korea
arxiv.org·1d
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A country of alien idiots in a datacenter: AI progress and public alarm
lesswrong.com·1d
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I've been trying to make a real production service that uses LLM and it turned into a pure agony. Here are some of my "experiences".
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MoSa: Motion Generation with Scalable Autoregressive Modeling
arxiv.org·4d
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flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
arxiv.org·4d
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SAIL-RL: Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning
arxiv.org·3d
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Jr. AI Scientist and Its Risk Report: Autonomous Scientific Exploration from a Baseline Paper
arxiv.org·1d
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Computed Tomography (CT)-derived Cardiovascular Flow Estimation Using Physics-Informed Neural Networks Improves with Sinogram-based Training: A Simulation Study
arxiv.org·1d
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Analysis of Iterative Deblurring: No Explicit Noise
arxiv.org·3d
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CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World
arxiv.org·4d
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Dynamic Model Selection for Trajectory Prediction via Pairwise Ranking and Meta-Features
arxiv.org·4d
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AI Progress Should Be Measured by Capability-Per-Resource, Not Scale Alone: A Framework for Gradient-Guided Resource Allocation in LLMs
arxiv.org·4d
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Escalation and perception
lesswrong.com·12h
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