代码大模型 / AI 编程

Learning to Complete Code with Sketches

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments Published in ICLR 2022

Learning logic programs through divide, constrain, and conquer

Andrew Cropper

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments Accepted for AAAI2022

DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion

Wei Niu, Jiexiong Guan, Yanzhi Wang, Gagan Agrawal, Bin Ren

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI、cs.LG

Solving Visual Analogies Using Neural Algorithmic Reasoning

Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments 20 pages. Contains extended abstract accepted at the AAAI-22 Student Abstract and Poster Program along with relevent supplementary material

Synthesizing Optimal Parallelism Placement and Reduction Strategies on Hierarchical Systems for Deep Learning

Ningning Xie, Tamara Norman, Dominik Grewe, Dimitrios Vytiniotis

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.LG、cs.PL

Neural-guided, Bidirectional Program Search for Abstraction and Reasoning

Simon Alford, Anshula Gandhi, Akshay Rangamani, Andrzej Banburski, Tony Wang, Sylee Dandekar, John Chin, Tomaso Poggio, Peter Chin

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments Published as a conference paper at Complex Networks 2021

A domain-specific modeling and analysis environment for complex IoT applications

Felicien Ihirwe, Davide Di Ruscio, Silvia Mazzini, Alfonso Pierantonio

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.PL

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy

Colin B. Clement, Shuai Lu, Xiaoyu Liu, Michele Tufano, Dawn Drain, Nan Duan, Neel Sundaresan, Alexey Svyatkovskiy

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments EMNLP 2021 camera ready

Parallel Constraint-Driven Inductive Logic Programming

Andrew Cropper, Oghenejokpeme Orhobor, Cristian Dinu, Rolf Morel

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments Paper under review

Multi-modal Program Inference: a Marriage of Pre-trainedLanguage Models and Component-based Synthesis

Kia Rahmani, Mohammad Raza, Sumit Gulwani, Vu Le, Daniel Morris, Arjun Radhakrishna, Gustavo Soares, Ashish Tiwari

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.PL

Comments To be published in OOPSLA 2021

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

Wei Niu, Zhengang Li, Xiaolong Ma, Peiyan Dong, Gang Zhou, Xuehai Qian, Xue Lin, Yanzhi Wang, Bin Ren

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI、cs.LG

Comments Accepted in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

Satisfiability and Synthesis Modulo Oracles

Elizabeth Polgreen, Andrew Reynolds, Sanjit A. Seshia

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.LG、cs.PL

Comments 12 pages, 8 Figures

Text2App: A Framework for Creating Android Apps from Text Descriptions

Masum Hasan, Kazi Sajeed Mehrab, Wasi Uddin Ahmad, Rifat Shahriyar

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL、cs.AI

Comments Submitted to EMNLP 2021 System Demonstrations

Data Analytics and Machine Learning Methods, Techniques and Tool for Model-Driven Engineering of Smart IoT Services

Armin Moin

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments ICSE Doctoral Symposium Paper

Journal ref IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), 2021

ThingML+ Augmenting Model-Driven Software Engineering for the Internet of Things with Machine Learning

Armin Moin, Stephan Rössler, Stephan Günnemann

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments Published in Proc. of the International Conference on Model Driven Engineering Languages and Systems (MODELS) 2018 Workshops (MDE4IoT)

Journal ref Proceedings of MODELS 2018 Workshops (MDE4IoT), co-located with the ACM/IEEE 21st International Conference on Model Driven Engineering Languages and Systems (MODELS), Copenhagen, Denmark, 2018

From Things' Modeling Language (ThingML) to Things' Machine Learning (ThingML2)

Armin Moin, Stephan Rössler, Marouane Sayih, Stephan Günnemann

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments International Conference on Model Driven Engineering Languages and Systems (MODELS) 2020 Poster Companion (Extended Abstract)

Journal ref Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2020

CoTexT: Multi-task Learning with Code-Text Transformer

Long Phan, Hieu Tran, Daniel Le, Hieu Nguyen, James Anibal, Alec Peltekian, Yanfang Ye

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI、cs.PL

Interpreting Expert Annotation Differences in Animal Behavior

Megan Tjandrasuwita, Jennifer J. Sun, Ann Kennedy, Swarat Chaudhuri, Yisong Yue

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments 4 pages, 5 figures, presented as a poster at CV4Animals workshop @ CVPR21

Towards a modeling and analysis environment for industrial IoT systems

Felicien Ihirwe, Davide Di Ruscio, Silvia Mazzini, Alfonso Pierantonio

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.PL

Comments 7 figures, 10 pages

A Sketch-Based Neural Model for Generating Commit Messages from Diffs

Nicolae-Teodor Pavel, Traian Rebedea

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.CL

Comments submitted at ASE 2019

Embedding Code Contexts for Cryptographic API Suggestion:New Methodologies and Comparisons

Ya Xiao, Salman Ahmed, Wenjia Song, Xinyang Ge, Bimal Viswanath, Danfeng Yao

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.AI

Comments 12 pages, 10 figures

IOT: Instance-wise Layer Reordering for Transformer Structures

Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL、cs.AI

Comments Accepted at ICLR-2021

Learning Differentially Private Mechanisms

Subhajit Roy, Justin Hsu, Aws Albarghouthi

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.LG、cs.PL

Taming the Expressiveness and Programmability of Graph Analytical Queries

Lu Qin, Longbin Lai, Kongzhang Hao, Zhongxin Zhou, Yiwei Zhao, Yuxing Han, Xuemin Lin, Zhengping Qian, Jingren Zhou

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL、cs.PL

Comments 22 pages

Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination?

Jieshan Chen, Mulong Xie, Zhenchang Xing, Chunyang Chen, Xiwei Xu, Liming Zhu, Guoqiang Li

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.LG

Comments 13 pages, accepted to ESEC/FSE '20

Code Building Genetic Programming

Edward Pantridge, Lee Spector

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.SE、cs.PL

Comments Proceedings of the 2020 Genetic and Evolutionary Computation Conference, Genetic Programming Track

Quantitatively Assessing the Benefits of Model-driven Development in Agent-based Modeling and Simulation

Fernando Santos, Ingrid Nunes, Ana L. C. Bazzan

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE、cs.AI

Journal ref Simulation Modelling Practice and Theory, v. 104, 1-19 (2020)

PLANS: Robust Program Learning from Neurally Inferred Specifications

Raphaël Dang-Nhu

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments 16 pages, 6 figures, 5 tables

Learning large logic programs by going beyond entailment

Andrew Cropper, Sebastijan Dumančić

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.AI、cs.LG

Comments IJCAI2020 paper

Comparison of Syntactic and Semantic Representations of Programs in Neural Embeddings

Austin P. Wright, Herbert Wiklicky

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.SE、cs.LG

Comments 54 Pages, Imperial College London Masters Thesis