awesome-program
github.com/shaohua0116/awesome-program ↗A curated list of papers related to program synthesis, program induction, program execution, program and code repair, and programmatic reinforcement learning.
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Curated Resources
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3 hours ago
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Program SynthesisProgram InductionProgram ExecutionProgram and Code RepairProgrammatic Reinforcement Learning
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Program Execution
- A Composable Specification Language for Reinforcement Learning Tasks
NeurIPS
- Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages
arXiv
- Learning to Execute
arXiv
- Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
NeurIPS
- Modular Multitask Reinforcement Learning with Policy Sketches
ICML
- Program Guided Agent
ICLR
Program Synthesis
- Ain’t Nobody Got Time For Coding: Structure-Aware Program Synthesis From Natural Language
arXiv
- A large-scale benchmark for few-shot program induction and synthesis
ICML
- Automatic Program Synthesis of Long Programs with a Learned Garbage Collector
NeurIPS
- CSGNet: Neural Shape Parser for Constructive Solid Geometry
CVPR
- DeepCoder: Learning to Write Programs
ICLR
- Differentiable Programs with Neural Libraries
ICML
Program Induction
- A large-scale benchmark for few-shot program induction and synthesis
ICML
- DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
arXiv
- Extensions and Limitations of the Neural GPU
arXiv
- Improving the Universality and Learnability of Neural Programmer-Interpreters with Combinator Abstraction
ICLR
- Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture
arXiv
- Learning Compositional Neural Programs with Recursive Tree Search and Planning
NeurIPS
Program and Code Repair
- Automated Program Repair
CACM
- Contract-Based Program Repair without the Contracts
ASE
- DLFix: Context-based Code Transformation Learning for Automated Program Repair
ICSE
- DynaMoth: Dynamic Code Synthesis for Automatic Program Repair
AST
- FixMiner: Mining Relevant Fix Patterns for Automated Program Repair
ESEJ
- Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
ICML
Programmatic Reinforcement Learning
- Discovering symbolic policies with deep reinforcement learning
ICML
- Imitation-Projected Programmatic Reinforcement Learning
NeurIPS
- Learning Finite State Representations of Recurrent Policy Networks
ICLR
- Learning to Synthesize Programs as Interpretable and Generalizable Policies
NeurIPS
- Neural logic reinforcement learning
ICML
- Programmable Reinforcement Learning Agents
NIPS
Showing a sample of 93 resources. View the full list on GitHub →