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Found 3 papers, 1 papers with code
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
We apply this approach to generate tens of thousands of validated training items for Julia, Lua, OCaml, R, and Racket.
MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation
Using these new parallel benchmarks, we evaluate the multi-language performance of three state-of-the-art code generation models: Codex, CodeGen, and InCoder.
Measure Transformer Semantics for Bayesian Machine Learning
The Bayesian approach to machine learning amounts to computing posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a prior distribution) and a set of observations of variables.
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