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研究Exposing Blind Spots in Deep Imbalanced Regression Evaluation(arxiv.org)
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研究Goal-driven Variant Categorization(arxiv.org)
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153
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研究EvidenT: Building Trustworthy Enterprise Assistants through Evidence Groundedness and Traceability(arxiv.org)
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研究An Affordable AI-Integrated Smart Cane for Multimodal Mobility Assistance of Visually Impaired Users(arxiv.org)
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研究Learning 3D biophysical cell properties from 2D images and cell-population statistics(arxiv.org)
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研究Social Influence and the Allocation of Scientific Attention in AI Populations(arxiv.org)
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研究Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach(arxiv.org)
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研究Dual-GNN Multilevel Coarsening for Maximum Independent Set(arxiv.org)
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159
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研究Entropy Can Flow, or It Can Guide. Be Entropy. LEDFlow: Introducing Entropy-guided Generation Order into Uniform Discrete Flow(arxiv.org)
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研究Stable Unsupervised Continual Chunking with Sheaf SyncMap(arxiv.org)
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研究Brain-Inspired Hierarchical Modularity for General Continual Learning(arxiv.org)
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研究Agreement Overstates Evidence: Error Dependence in LLM Judge Consensus(arxiv.org)
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研究The Wisdom of Artificial Deliberative Crowds(arxiv.org)
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研究Roundtables: The Deadly Failures of The Virtual Border Wall(technologyreview.com)
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研究Debating RSI, the US-China Gap, and Jaggedness with JS Denain of Epoch AI(interconnects.ai)
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研究The Sequence Knowledge - Issue 937: RSI in Post-Training: The Loop That Already Shipped(thesequence.substack.com)
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研究How UK AISI and EvalEval Are Making Benchmark Results Reproducible(huggingface.co)
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jack-clark.net
研究Import AI 473: The US’s superintelligence strategy; human brain in a mouse skull; and machine hermeneutics(jack-clark.net)
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研究The Download: investigating deaths at the US border’s “virtual wall”(technologyreview.com)
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研究4 ways to address the failures we found along the US border’s “virtual wall”(technologyreview.com)
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研究She died at the San Diego border. A surveillance camera was in plain sight(technologyreview.com)
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研究The current balance of power in open models(interconnects.ai)
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研究When AI Reviews Train AI Reviewers: Scientific-Judgment Collapse and Mitigation(arxiv.org)
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研究Scaling Discovery through Test-Time Communication(arxiv.org)
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研究Efficient Bayes-Adaptive Reinforcement Learning with Temporal Logic Specifications(arxiv.org)
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研究MOSAIC-SR: Transformer-Guided Symbolic Regression for Scientific Equation Recovery(arxiv.org)
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研究Generative inversion for early ranking of competing geologic interpretations(arxiv.org)
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研究Attention-Aware Routing: Coupling Routing and Attention in MoEs(arxiv.org)
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研究Elastic Threshold Attention: Learned Contextual Sparsity for Long-Context Decoding(arxiv.org)
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研究Sparse Priors for Efficient Distribution Learning(arxiv.org)
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