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Found 6 papers, 2 papers with code
Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsiveness, and the enabling of autonomous operations.
Analyzing Intentional Behavior in Autonomous Agents under Uncertainty
We say that there is evidence of intentional behavior if the scope of agency is high and the decisions of the agent are close to being optimal for reaching the event.
Repairing Bugs in Python Assignments Using Large Language Models
We propose to use a large language model trained on code, such as Codex, to build an APR system -- MMAPR -- for introductory Python programming assignments.
Succinct Explanations With Cascading Decision Trees
The decision tree is one of the most popular and classical machine learning models from the 1980s.
Grammar Filtering For Syntax-Guided Synthesis
By preprocessing SyGuS PBE problems with a neural network, we can use a data driven approach to reduce the size of the search space, then allow automated reasoning-based solvers to more quickly find a solution analytically.
Temporal Stream Logic: Synthesis beyond the Bools
On the other hand, however, synthesis from TSL is scalable, because it is independent of the complexity of the handled data.
Logic in Computer Science
