CodePlan: Repository-level Coding using LLMs and Planning
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2309.12499
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73
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Octopus: Embodied Vision-Language Programmer from Environmental Feedback
Paper • 2310.08588 • Published • 34 -
SALMON: Self-Alignment with Principle-Following Reward Models
Paper • 2310.05910 • Published • 2 -
Lemur: Harmonizing Natural Language and Code for Language Agents
Paper • 2310.06830 • Published • 30 -
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
Paper • 2309.10691 • Published • 4 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 134 -
StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback
Paper • 2402.01391 • Published • 41 -
Creative Robot Tool Use with Large Language Models
Paper • 2310.13065 • Published • 8 -
AgileCoder: Dynamic Collaborative Agents for Software Development based on Agile Methodology
Paper • 2406.11912 • Published • 26 -
SemCoder: Training Code Language Models with Comprehensive Semantics
Paper • 2406.01006 • Published -
AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct
Paper • 2405.14906 • Published • 23 -
Training LLMs to Better Self-Debug and Explain Code
Paper • 2405.18649 • Published -
InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct
Paper • 2407.05700 • Published • 9 -
ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
Paper • 2405.17057 • Published -
PLUM: Preference Learning Plus Test Cases Yields Better Code Language Models
Paper • 2406.06887 • Published • 1 -
McEval: Massively Multilingual Code Evaluation
Paper • 2406.07436 • Published • 39