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Department of Civil and Environmental Engineering, Rice University, Houston, TX
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Learning TSP through a structured latent object reveals critical Hamiltonian insights that improve both tour quality and interpretability.
Training data diversity is the secret sauce that boosts agentic model performance, with OpenThoughts-Agent achieving a notable accuracy leap over existing benchmarks.
Current AI assistants struggle to understand your mood swings across multiple conversations, and A-MBER exposes this gap.
Graph condensation, while shrinking massive datasets for GNN training, can inadvertently amplify biases – until now.