Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Program synthesis or code generation aims to generate a program that satisfies a problem specification. Recent approaches using large-scale pretrained language models (LMs) have shown promising results, yet they have som…
Code GenerationDecoderDeep Reinforcement Learningmbpp+3GitHub Copilot AI pair programmer: Asset or Liability?
Automatic program synthesis is a long-lasting dream in software engineering. Recently, a promising Deep Learning (DL) based solution, called Copilot, has been proposed by OpenAI and Microsoft as an industrial product. Al…
Program SynthesisFrom Perception to Programs: Regularize, Overparameterize, and Amortize
Toward combining inductive reasoning with perception abilities, we develop techniques for neurosymbolic program synthesis where perceptual input is first parsed by neural nets into a low-dimensional interpretable represe…
Program SynthesisFrom Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams
A final exam in machine learning at a top institution such as MIT, Harvard, or Cornell typically takes faculty days to write, and students hours to solve. We demonstrate that large language models pass machine learning f…
BIG-bench Machine LearningFew-Shot LearningLanguage ModellingMultiple-choice+2Functional Code Building Genetic Programming
General program synthesis has become an important application area for genetic programming (GP), and for artificial intelligence more generally. Code Building Genetic Programming (CBGP) is a recently introduced GP method…
BenchmarkingProgram SynthesisLearning logic programs by combining programs
The goal of inductive logic programming is to induce a logic program (a set of logical rules) that generalises training examples. Inducing programs with many rules and literals is a major challenge. To tackle this challe…
Inductive logic programmingProgram SynthesisThe Environmental Discontinuity Hypothesis for Down-Sampled Lexicase Selection
Down-sampling training data has long been shown to improve the generalization performance of a wide range of machine learning systems. Recently, down-sampling has proved effective in genetic programming (GP) runs that ut…
Program SynthesisLearning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions
Pretrained language models have shown superior performance on many natural language processing tasks, yet they still struggle at multi-step formal reasoning tasks like grade school math problems. One key challenge of fin…
Arithmetic ReasoningEfficient ExplorationGSM8KMath+1GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis
Despite achieving superior performance in human-level control problems, unlike humans, deep reinforcement learning (DRL) lacks high-order intelligence (e.g., logic deduction and reuse), thus it behaves ineffectively than…
Decision MakingDeep Reinforcement LearningProgram Synthesisreinforcement-learning+2Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis
We propose a new approach to automated theorem proving where an AlphaZero-style agent is self-training to refine a generic high-level expert strategy expressed as a nondeterministic program. An analogous teacher agent is…
Automated Theorem ProvingProgram SynthesisAutoTSG: Learning and Synthesis for Incident Troubleshooting
Incident management is a key aspect of operating large-scale cloud services. To aid with faster and efficient resolution of incidents, engineering teams document frequent troubleshooting steps in the form of Troubleshoot…
4kManagementProgram SynthesisAutoformalization with Large Language Models
Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could advance the fields of formal verification, …
Automated Theorem ProvingProgram SynthesisTransformer-based Program Synthesis for Low-Data Environments
Recent advancements in large pre-trained transformer models (GPT2/3, T5) have found use in program synthesis to generate programs that satisfy a set of input/output examples. However, these models perform poorly on long-…
Program SynthesisNeural Program Synthesis with Query
Aiming to find a program satisfying the user intent given input-output examples, program synthesis has attracted increasing interest in the area of machine learning. Despite the promising performance of existing methods,…
Program SynthesisFrom {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in …
MisconceptionsProgram SynthesisExample-based Synthesis of Static Analysis Rules
Static Analysis tools have rules for several code quality issues and these rules are created by experts manually. In this paper, we address the problem of automatic synthesis of code quality rules from examples. We formu…
Program SynthesisWhat If: Generating Code to Answer Simulation Questions
Many texts, especially in chemistry and biology, describe complex processes. We focus on texts that describe a chemical reaction process and questions that ask about the process's outcome under different environmental co…
Program SynthesisSemantic SimilaritySemantic Textual SimilarityPopulation Diversity Leads to Short Running Times of Lexicase Selection
In this paper we investigate why the running time of lexicase parent selection is empirically much lower than its worst-case bound of O(N*C). We define a measure of population diversity and prove that high diversity lead…
DiversityProgram SynthesisInCoder: A Generative Model for Code Infilling and Synthesis
Code is seldom written in a single left-to-right pass and is instead repeatedly edited and refined. We introduce InCoder, a unified generative model that can perform program synthesis (via left-to-right generation) as we…
Code GenerationComment GenerationProgram SynthesisLandmarks and Regions: A Robust Approach to Data Extraction
We propose a new approach to extracting data items or field values from semi-structured documents. Examples of such problems include extracting passenger name, departure time and departure airport from a travel itinerary…
Program Synthesis