Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
Automated Decision-based Adversarial Attacks
Deep learning models are vulnerable to adversarial examples, which can fool a target classifier by imposing imperceptible perturbations onto natural examples. In this work, we consider the practical and challenging decis…
Adversarial AttackProgram SynthesisInductive Program Synthesis over Noisy Datasets using Abstraction Refinement Based Optimization
We present a new synthesis algorithm to solve program synthesis over noisy datasets, i.e., data that may contain incorrect/corrupted input-output examples. Our algorithm uses an abstraction refinement based optimization …
Program SynthesisToward Code Generation: A Survey and Lessons from Semantic Parsing
With the growth of natural language processing techniques and demand for improved software engineering efficiency, there is an emerging interest in translating intention from human languages to programming languages. In …
Code GenerationProgram SynthesisSemantic ParsingSurveyCodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing
Currently, a growing number of mature natural language processing applications make people's life more convenient. Such applications are built by source code - the language in software engineering. However, the applicati…
API Sequence RecommendationCode Comment GenerationCode Documentation GenerationCode Generation+7Geometry of Program Synthesis
We re-evaluate universal computation based on the synthesis of Turing machines. This leads to a view of programs as singularities of analytic varieties or, equivalently, as phases of the Bayesian posterior of a synthesis…
Program SynthesisToward Neural-Network-Guided Program Synthesis and Verification
We propose a novel framework of program and invariant synthesis called neural network-guided synthesis. We first show that, by suitably designing and training neural networks, we can extract logical formulas over integer…
Program SynthesisProgram Synthesis Over Noisy Data with Guarantees
We explore and formalize the task of synthesizing programs over noisy data, i.e., data that may contain corrupted input-output examples. By formalizing the concept of a Noise Source, an Input Source, and a prior distribu…
Program SynthesisA Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics
Inspired by humans' exceptional ability to master arithmetic and generalize to new problems, we present a new dataset, Handwritten arithmetic with INTegers (HINT), to examine machines' capability of learning generalizabl…
Few-Shot LearningProgram SynthesisSystematic GeneralizationProgram Synthesis Guided Reinforcement Learning for Partially Observed Environments
A key challenge for reinforcement learning is solving long-horizon planning problems. Recent work has leveraged programs to guide reinforcement learning in these settings. However, these approaches impose a high manual b…
MinecraftProgram Synthesisreinforcement-learningReinforcement Learning+1Refinement Type Directed Search for Meta-Interpretive-Learning of Higher-Order Logic Programs
The program synthesis problem within the Inductive Logic Programming (ILP) community has typically been seen as untyped. We consider the benefits of user provided types on background knowledge. Building on the Meta-Inter…
Inductive logic programmingProgram SynthesisReport of the Workshop on Program Synthesis for Scientific Computing
Program synthesis is an active research field in academia, national labs, and industry. Yet, work directly applicable to scientific computing, while having some impressive successes, has been limited. This report reviews…
Program SynthesisBF++: a language for general-purpose program synthesis
Most state of the art decision systems based on Reinforcement Learning (RL) are data-driven black-box neural models, where it is often difficult to incorporate expert knowledge into the models or let experts review and v…
Decision MakingOpenAI GymProgram SynthesisReinforcement Learning (RL)Analysis of Evolutionary Program Synthesis for Card Games
In this report, we inspect the application of an evolutionary approach to the game of Rack'O, which is a card game revolving around the notion of decision making. We first apply the evolutionary technique for obtaining a…
Card GamesDecision MakingProgram SynthesisLearning Differentially Private Mechanisms
Differential privacy is a formal, mathematical definition of data privacy that has gained traction in academia, industry, and government. The task of correctly constructing differentially private algorithms is non-trivia…
Program SynthesisNeurosymbolic Deep Generative Models for Sequence Data with Relational Constraints
Recently, there has been significant progress designing deep generative models that generate realistic sequence data such as text or music. Nevertheless, it remains difficult to incorporate high-level structure to guide …
Program SynthesisFCR: Flow Chart Recognition Network for Program Synthesis
Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from images of flow chart that serve as accurate and i…
Program SynthesisVisible and Invisible: Causal Variable Learning and its Application in a Cancer Study
Causal visual discovery is a fundamental yet challenging problem in many research fields. Given visual data and the outcome of interest, the goal is to infer the cause-effect relation. Aside from rich visual ('visible') …
Program SynthesisRepresenting Partial Programs with Blended Abstract Semantics
Synthesizing programs from examples requires searching over a vast, combinatorial space of possible programs. In this search process, a key challenge is representing the behavior of a partially written program before it …
Program SynthesisTag-based regulation of modules in genetic programming improves context-dependent problem solving
We introduce and experimentally demonstrate the utility of tag-based genetic regulation, a new genetic programming (GP) technique that allows programs to dynamically adjust which code modules to express. Tags are evolvab…
Program SynthesisTAGPLANS: Neuro-Symbolic Program Learning from Videos
Recent years have seen the rise of statistical program learning based on neural models as an alternative to traditional rule-based systems for programming by example. Rule-based approaches offer correctness guarantees in…
Program Synthesis