Empirical Judgments
2 papers with code • 1 benchmarks • 1 datasets
Drawing inspiration from Immanuel Kant, this task measures a model’s ability to distinguish between two kinds of empirical judgments: judgments that assert a correlative relation between empirical events, and judgments that assert a causal relation.
Source: BIG-bench
Benchmarks
These leaderboards are used to track progress in Empirical Judgments
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BIG-bench
Most implemented papers
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Training Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
