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 301–350 of 423 papers

TitleStatusHype
Program Synthesis as Dependency Quantified Formula Modulo TheoryCode0
Automated Decision-based Adversarial Attacks—0
Inductive Program Synthesis over Noisy Datasets using Abstraction Refinement Based Optimization—0
Toward Code Generation: A Survey and Lessons from Semantic Parsing—0
Geometry of Program Synthesis—0
Toward Neural-Network-Guided Program Synthesis and VerificationCode0
Program Synthesis Over Noisy Data with Guarantees—0
A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics—0
Refinement Type Directed Search for Meta-Interpretive-Learning of Higher-Order Logic Programs—0
Report of the Workshop on Program Synthesis for Scientific Computing—0
BF++: a language for general-purpose program synthesisCode0
Analysis of Evolutionary Program Synthesis for Card GamesCode0
Learning Differentially Private Mechanisms—0
FCR: Flow Chart Recognition Network for Program Synthesis—0
Visible and Invisible: Causal Variable Learning and its Application in a Cancer Study—0
Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints—0
Representing Partial Programs with Blended Abstract Semantics—0
Tag-based regulation of modules in genetic programming improves context-dependent problem solvingCode0
Latent Programmer: Discrete Latent Codes for Program Synthesis—0
PLANS: Neuro-Symbolic Program Learning from Videos—0
Multi-Plane Program Induction with 3D Box Priors—0
GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts—0
Learning to Execute Programs with Instruction Pointer Attention Graph Neural NetworksCode0
Dreaming with ARC—0
Automated Generation of Executable Cross-Language Background Knowledge—0
Goal-directed Generation of Discrete Structures with Conditional Generative Models—0
Optimal Neural Program Synthesis from Multimodal Specifications—0
Adversarial Synthetic Datasets for Neural Program Synthesis—0
Type-driven Neural Programming by Example—0
Process Discovery for Structured Program Synthesis—0
Robot Action Selection Learning via Layered Dimension Informed Program SynthesisCode0
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration—0
Semi-supervised Learning From Demonstration Through Program Synthesis: An Inspection Robot Case Study—0
Synthesize, Execute and Debug: Learning to Repair for Neural Program SynthesisCode0
Programming by Rewards—0
Program Synthesis with Pragmatic Communication—0
Learning Web-based Procedures by Reasoning over Explanations and Demonstrations in Context—0
Information-theoretic User Interaction: Significant Inputs for Program Synthesis—0
Neural Program Synthesis with a Differentiable Fixer—0
IReEn: Reverse-Engineering of Black-Box Functions via Iterative Neural Program Synthesis—0
PLANS: Robust Program Learning from Neurally Inferred SpecificationsCode0
Learning large logic programs by going beyond entailment—0
Knowledge Refactoring for Inductive Program SynthesisCode0
Creating Synthetic Datasets via Evolution for Neural Program Synthesis—0
Evaluating Sequence-to-Sequence Learning Models for If-Then Program SynthesisCode0
Unsupervised Program Synthesis for Images By Sampling Without Replacement—0
CounterExample Guided Neural Synthesis—0
Generating Programmatic Referring Expressions via Program SynthesisCode0
Towards Neural-Guided Program Synthesis for Linear Temporal Logic Specifications—0
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence GenerationCode0
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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