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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots ... Zhao, Wenting; Liu, Ye; Wan, Yao. - : arXiv, 2022 BASE Show details 2 Compilable Neural Code Generation with Compiler Feedback ... Wang, Xin; Wang, Yasheng; Wan, Yao; Mi, Fei; Li, Yitong; Zhou, Pingyi; Liu, Jin; Wu, Hao; Jiang, Xin; Liu, Qun. - : arXiv, 2022 Abstract: Automatically generating compilable programs with (or without) natural language descriptions has always been a touchstone problem for computational linguistics and automated software engineering. Existing deep-learning approaches model code generation as text generation, either constrained by grammar structures in decoder, or driven by pre-trained language models on large-scale code corpus (e.g., CodeGPT, PLBART, and CodeT5). However, few of them account for compilability of the generated programs. To improve compilability of the generated programs, this paper proposes COMPCODER, a three-stage pipeline utilizing compiler feedback for compilable code generation, including language model fine-tuning, compilability reinforcement, and compilability discrimination. Comprehensive experiments on two code generation tasks demonstrate the effectiveness of our proposed approach, improving the success rate of compilation from 44.18 to 89.18 in code completion on average and from 70.3 to 96.2 in text-to-code generation, ... : Accepted by ACL 2022 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Programming Languages cs.PL URL: https://arxiv.org/abs/2203.05132 https://dx.doi.org/10.48550/arxiv.2203.05132 BASE Hide details 3 HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; He, Lifang; LIU, YE. - : Underline Science Inc., 2021 BASE Show details 4 Disentangled Code Representation Learning for Multiple Programming Languages ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hong, Haiwen; LIU, YE. - : Underline Science Inc., 2021 BASE Show details 5 Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ... The 28th International Conference on Computational Linguistics 2020; Hashimoto, Kazuma; Socher, Richard. - : Underline Science Inc., 2020 BASE Show details 6 Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking ... Zhang, Jian-Guo; Hashimoto, Kazuma; Wu, Chien-Sheng. - : arXiv, 2019 BASE Show details

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