Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
Solving Linear Algebra by Program Synthesis
We solve MIT's Linear Algebra 18.06 course and Columbia University's Computational Linear Algebra COMS3251 courses with perfect accuracy by interactive program synthesis. This surprisingly strong result is achieved by tu…
MathProgram SynthesisZero-Shot LearningSolving Linear Algebra by Program Synthesis
We solve MIT's Linear Algebra 18.06 course and Columbia University's Computational Linear Algebra COMS3251 courses with perfect accuracy by interactive program synthesis. This surprisingly strong result is achieved by tu…
MathProgram SynthesisZero-Shot LearningSolving Probability and Statistics Problems by Program Synthesis
We solve university level probability and statistics questions by program synthesis using OpenAI's Codex, a Transformer trained on text and fine-tuned on code. We transform course problems from MIT's 18.05 Introduction t…
FormProgram SynthesisPrompt EngineeringChoose Your Programming Copilot: A Comparison of the Program Synthesis Performance of GitHub Copilot and Genetic Programming
GitHub Copilot, an extension for the Visual Studio Code development environment powered by the large-scale language model Codex, makes automatic program synthesis available for software developers. This model has been ex…
Language ModelingLanguage ModellingProgram SynthesisExplainable Natural Language to Bash Translation using Abstract Syntax Tree
Natural language processing for program synthesis has been widely researched. In this work, we focus on generating Bash commands from natural language invocations with explanations. We propose a novel transformer based s…
Program SynthesisTranslationFew-Shot Novel Concept Learning for Semantic Parsing
Humans are capable of learning novel concepts from very few examples; in contrast, state-of-the-art machine learning algorithms typically need thousands of examples to do so. In this paper, we propose an algorithm for le…
Novel ConceptsProgram SynthesisSemantic ParsingScaling Neural Program Synthesis with Distribution-based Search
We consider the problem of automatically constructing computer programs from input-output examples. We investigate how to augment probabilistic and neural program synthesis methods with new search algorithms, proposing a…
Program SynthesisNeural-guided, Bidirectional Program Search for Abstraction and Reasoning
One of the challenges facing artificial intelligence research today is designing systems capable of utilizing systematic reasoning to generalize to new tasks. The Abstraction and Reasoning Corpus (ARC) measures such a ca…
ARCProgram SynthesisVisual ReasoningSynthesizing Optimal Parallelism Placement and Reduction Strategies on Hierarchical Systems for Deep Learning
We present a novel characterization of the mapping of multiple parallelism forms (e.g. data and model parallelism) onto hierarchical accelerator systems that is hierarchy-aware and greatly reduces the space of software-t…
GPUProgram SynthesisUsing Program Synthesis and Inductive Logic Programming to solve Bongard Problems
The ability to recognise and make analogies is often used as a measure or test of human intelligence. The ability to solve Bongard problems is an example of such a test. It has also been postulated that the ability to ra…
Inductive logic programmingProgram SynthesisSolving the Families In the Wild Kinship Verification Challenge by Program Synthesis
Kinship verification is the task of determining whether a parent-child, sibling, or grandparent-grandchild relationship exists between two people and is important in social media applications, forensic investigations, fi…
Kinship VerificationProgram SynthesisAutumnSynth: Synthesis of Reactive Programs with Structured Latent State
The human ability to efficiently discover causal theories of their environments from observations is a feat of nature that remains elusive in machines. In this work, we attempt to make progress on this frontier by formul…
Program SynthesisAre Transformers All That Karel Needs?
Recent works have shown the incredible promise of using neural networks for the task of program synthesis from input-output examples. In this paper, we propose using Transformer-based architectures as a baseline for the …
AllDecoderProgram SynthesisAutoCoder: Leveraging Transformers for Automatic Code Synthesis
Program synthesis from natural language descriptions is a challenging task. This paper explores two variants of transformer models for the task of program synthesis and showcase higher performance than the existing SOTA …
Program SynthesisAdversarial Robustness of Program Synthesis Models
The resurgence of automatic program synthesis has been observed with the rise of deep learning. In this paper, we study the behaviour of the program synthesis model under adversarial settings. Our experiments suggest tha…
Adversarial RobustnessProgram SynthesisA Genetic Programming Approach To Zero-Shot Neural Architecture Ranking
Neural networks are becoming increasingly ubiquitous in a wide range of use cases. A primary hurdle in deploying neural networks in many scenarios is the tedious and difficult neural network architectural design process,…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)image-classificationImage Classification+4Towards Physical, Imperceptible Adversarial Attacks via Adversarial Programs
Adversarial examples were originally defined as imperceptible perturbations which cause a deep neural network to misclassify. However, the majority of imperceptible perturbation attacks require to perturb a large number …
Program SynthesisLearning logic programs through divide, constrain, and conquer
We introduce an inductive logic programming approach that combines classical divide-and-conquer search with modern constraint-driven search. Our anytime approach can learn optimal, recursive, and large programs and suppo…
Inductive logic programmingProgram SynthesisParallel Constraint-Driven Inductive Logic Programming
Multi-core machines are ubiquitous. However, most inductive logic programming (ILP) approaches use only a single core, which severely limits their scalability. To address this limitation, we introduce parallel techniques…
Inductive logic programmingProgram SynthesisMulti-modal Program Inference: a Marriage of Pre-trainedLanguage Models and Component-based Synthesis
Multi-modal program synthesis refers to the task of synthesizing programs (code) from their specification given in different forms, such as a combination of natural language and examples. Examples provide a precise but i…
Program Synthesis