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Found 4 papers, 1 papers with code
Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training
Hyperparameter tuning of deep learning models can lead to order-of-magnitude performance gains for the same amount of compute.
Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety
Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and text summarization.
Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
As a benchmark tailored for studying RL generalization, we introduce Avalon, a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards.
Cross-Correlation of Planck CMB Lensing with DESI-Like LRGs
Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy physics, and test theories of modified gravity.
Cosmology and Nongalactic Astrophysics
