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Found 4 papers, 2 papers with code
tinyBenchmarks: evaluating LLMs with fewer examples
The versatility of large language models (LLMs) led to the creation of diverse benchmarks that thoroughly test a variety of language models' abilities.
Learning Latent and Hierarchical Structures in Cognitive Diagnosis Models
Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models that are widely used in modern educational, psychological, social and biological sciences.
Identifiability of Hierarchical Latent Attribute Models
The key ingredients of an HLAM include a binary structural matrix and a directed acyclic graph specifying hierarchical constraints on the configurations of latent attributes.
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models
Structured latent attribute models (SLAMs) are a special family of discrete latent variable models widely used in social and biological sciences.
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