Synthetic Data Characterization via Training Dynamics
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New papers, breakthroughs and academic AI research
AHMAD: Adaptive Hybrid Multi-task Vision Learning with Assisted Distillation for Keypoint Detection
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Reconstructing the Right Episode: Evaluating Interleaved Conversational Memory Beyond Long Context
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Simultaneous Envy and Equitability Guarantees
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rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
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Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach
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Equivariant Sheaf Neural Networks: Learning Geometric Transport on Graphs
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Geometry-aware Latent Autoregressive Generative Model for PDEs in Complex Domains
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Principal Component Regression Dominates all Monotone Spectral Filters for Linear Regression
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Revisit to Segment: Working Memory Distillation for Reasoning Segmentation
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Dec-BFTRL: Squre-Root Regret for Decentralized Online Upper-Linearizable Optimization under Separation Access with Application to Continuous Submodular Maximization
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Attention Is All You Need (to Avoid Spurious Oscillations)
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