SOTAVerified

Program Synthesis

Program synthesis is the process of automatically generating a program or code snippet that satisfies a given specification or set of requirements. This can include generating code from a formal specification, a natural language description, or example inputs and outputs. The primary goal of program synthesis is to minimize human intervention in the coding process, reduce errors, and improve productivity.

Program synthesis often involves the use of advanced algorithms, artificial intelligence, and machine learning techniques to search the space of possible programs that meet the given constraints. This process can be guided by a variety of techniques, such as constraint solving, symbolic execution, and genetic algorithms.

Papers

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Showing 151–175 of 423 papers

TitleStatusHype
GitHub Copilot AI pair programmer: Asset or Liability?Code0
Learning to Parallelize with OpenMP by Augmented Heterogeneous AST RepresentationCode0
Making sense of sensory inputCode0
Coffee: Boost Your Code LLMs by Fixing Bugs with FeedbackCode0
Learning to Execute Programs with Instruction Pointer Attention Graph Neural NetworksCode0
Generating Programmatic Referring Expressions via Program SynthesisCode0
Generating Pragmatic Examples to Train Neural Program SynthesizersCode0
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generatorsCode0
Learning to Infer Graphics Programs from Hand-Drawn ImagesCode0
Learning logic programs by combining programsCode0
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem ProvingCode0
Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning EnvironmentsCode0
NAPS: Natural Program Synthesis DatasetCode0
Learning to Infer Program SketchesCode0
ConceptSearch: Towards Efficient Program Search Using LLMs for Abstraction and Reasoning Corpus (ARC)Code0
Learning logic programs by discovering higher-order abstractionsCode0
Learning logic programs by discovering where not to searchCode0
From Solution Synthesis to Student Attempt Synthesis for Block-Based Visual Programming TasksCode0
Knowledge Refactoring for Inductive Program SynthesisCode0
Large Language Models Synergize with Automated Machine LearningCode0
Learning logic programs through divide, constrain, and conquerCode0
Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardwareCode0
Knowledge-Driven Program Synthesis via Adaptive Replacement Mutation and Auto-constructed Subprogram ArchivesCode0
Knowledge-Driven Robot Program Synthesis from Human VR DemonstrationsCode0
Learning MDL logic programs from noisy dataCode0
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All datasetsSPoC TestPSPoC TestWAlgoLisp

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DrRepairSuccess rate @budget 10038.5—Unverified
2Multiclass localizerSuccess rate @budget 10034.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DrRepairSuccess rate @budget 10057—Unverified
2Multiclass localizerSuccess rate @budget 10053.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CodeTrans-MT-TF-SmallAccuracy90.31—Unverified