InterCode
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A framework treating interactive coding as a reinforcement learning environment.
Interactive paradigm: Moves beyond static sequence-to-sequence coding benchmarks to multi-turn interactive coding with execution feedback.
Standardized RL environment: Provides Bash, SQL, and Python environments with consistent APIs for training and evaluating code agents.
Feedback-loop evaluation: Tests whether models can use execution errors, test failures, and intermediate outputs to iteratively improve their code.
Code-agent foundation: Anticipated and enabled the 2024 explosion of interactive coding agents (SWE-agent, OpenDevin, Aider) that leverage execution feedback loops.
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