Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
Program Synthesis and Semantic Parsing with Learned Code Idioms
Program synthesis of general-purpose source code from natural language specifications is challenging due to the need to reason about high-level patterns in the target program and low-level implementation details at the s…
Code GenerationProgram SynthesisSemantic ParsingSPoC: Search-based Pseudocode to Code
We consider the task of mapping pseudocode to long programs that are functionally correct. Given test cases as a mechanism to validate programs, we search over the space of possible translations of the pseudocode to find…
Program SynthesisTranslationWrite, Execute, Assess: Program Synthesis with a REPL
We present a neural program synthesis approach integrating components which write, execute, and assess code to navigate the search space of possible programs. We equip the search process with an interpreter or a read-eva…
NavigateProgram SynthesisOne-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis
Our interest in this paper is in meeting a rapidly growing industrial demand for information extraction from images of documents such as invoices, bills, receipts etc. In practice users are able to provide a very small n…
Program SynthesisSynthesizing Datalog Programs Using Numerical Relaxation
The problem of learning logical rules from examples arises in diverse fields, including program synthesis, logic programming, and machine learning. Existing approaches either involve solving computationally difficult com…
parameter estimationProgram SynthesisComparing and Combining Lexicase Selection and Novelty Search
Lexicase selection and novelty search, two parent selection methods used in evolutionary computation, emphasize exploring widely in the search space more than traditional methods such as tournament selection. However, le…
DiversityProgram SynthesisLearning a Meta-Solver for Syntax-Guided Program Synthesis
We study a general formulation of program synthesis called syntax-guided synthesis(SyGuS) that concerns synthesizing a program that follows a given grammar and satisfies a given logical specification. Both the logical sp…
Graph Neural NetworkMeta-LearningProgram SynthesisReinforcement LearningExecution-Guided Neural Program Synthesis
Neural program synthesis from input-output examples has attracted an increasing interest from both the machine learning and the programming language community. Most existing neural program synthesis approaches employ an …
DecoderProgram Synthesis"Why did you do that?": Explaining black box models with Inductive Synthesis
By their nature, the composition of black box models is opaque. This makes the ability to generate explanations for the response to stimuli challenging. The importance of explaining black box models has become increasing…
Program SynthesisNeural Program Planner for Structured Predictions
We consider the problem of weakly supervised structured prediction (SP) with reinforcement learning (RL) – for example, given a database table and a question, perform a sequence of computation actions on the table, which…
Machine TranslationProgram SynthesisQuestion AnsweringReinforcement Learning (RL)+2Learning to Infer Program Sketches
Our goal is to build systems which write code automatically from the kinds of specifications humans can most easily provide, such as examples and natural language instruction. The key idea of this work is that a flexible…
MemorizationProgram SynthesisLearning Neurosymbolic Generative Models via Program Synthesis
Significant strides have been made toward designing better generative models in recent years. Despite this progress, however, state-of-the-art approaches are still largely unable to capture complex global structure in da…
Program SynthesisA Survey on Semantic Parsing
A significant amount of information in today's world is stored in structured and semi-structured knowledge bases. Efficient and simple methods to query them are essential and must not be restricted to only those who have…
Program SynthesisSemantic ParsingSurveyImproving Neural Program Synthesis with Inferred Execution Traces
The task of program synthesis, or automatically generating programs that are consistent with a provided specification, remains a challenging task in artificial intelligence. As in other fields of AI, deep learning-based …
Program SynthesisStepping Stones to Inductive Synthesis of Low-Level Looping Programs
Inductive program synthesis, from input/output examples, can provide an opportunity to automatically create programs from scratch without presupposing the algorithmic form of the solution. For induction of general progra…
Program SynthesisAin't Nobody Got Time For Coding: Structure-Aware Program Synthesis From Natural Language
Program synthesis from natural language (NL) is practical for humans and, once technically feasible, would significantly facilitate software development and revolutionize end-user programming. We present SAPS, an end-to-…
DecoderProgram SynthesisSentenceInference Over Programs That Make Predictions
This abstract extends on the previous work (arXiv:1407.2646, arXiv:1606.00075) on program induction using probabilistic programming. It describes possible further steps to extend that work, such that, ultimately, automat…
Probabilistic ProgrammingProgram inductionProgram SynthesisSemRegex: A Semantics-Based Approach for Generating Regular Expressions from Natural Language Specifications
Recent research proposes syntax-based approaches to address the problem of generating programs from natural language specifications. These approaches typically train a sequence-to-sequence learning model using a syntax-b…
Program SynthesisNovel positional encodings to enable tree-structured transformers
With interest in program synthesis and similarly flavored problems rapidly increasing, neural models optimized for tree-domain problems are of great value. In the sequence domain, transformers can learn relationships acro…
Program SynthesisSemantic ParsingTranslationAutomatic Program Synthesis of Long Programs with a Learned Garbage Collector
We consider the problem of generating automatic code given sample input-output pairs. We train a neural network to map from the current state and the outputs to the program's next statement. The neural network optimizes …
Program Synthesis