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Found 6 papers, 4 papers with code
PhilHumans: Benchmarking Machine Learning for Personal Health
The use of machine learning in Healthcare has the potential to improve patient outcomes as well as broaden the reach and affordability of Healthcare.
Intensive Care as One Big Sequence Modeling Problem
Reinforcement Learning in Healthcare is typically concerned with narrow self-contained tasks such as sepsis prediction or anesthesia control.
Fully Autonomous Programming with Large Language Models
Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metrics or human evaluation), but achieve a low or even zero accuracy as measured by unit tests due to small imperfections, such as the wrong input or output format.
Autoencoders as Tools for Program Synthesis
Recently there have been many advances in research on language modeling of source code.
Neurogenetic Programming Framework for Explainable Reinforcement Learning
Automatic programming, the task of generating computer programs compliant with a specification without a human developer, is usually tackled either via genetic programming methods based on mutation and recombination of programs, or via neural language models.
BF++: a language for general-purpose program synthesis
Most state of the art decision systems based on Reinforcement Learning (RL) are data-driven black-box neural models, where it is often difficult to incorporate expert knowledge into the models or let experts review and validate the learned decision mechanisms.
