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ChatGPT has revolutionized many research and industrial fields.
Refactoring workbook
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Deep Reinforcement Learning from Human Preferences. In Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS’17) . Curran Associates Inc., Red Hook, NY, USA, 4302–4310
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A Systematic Evaluation of Static API-Misuse Detectors
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Measuring catastrophic forgetting in neural networks. In Proceedings of the AAAI conference on artificial intelligence , Vol. 32
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Code smells and refactoring: A tertiary systematic review of challenges and observations
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Anatomy of catastrophic forgetting: Hidden representations and task semantics
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Can OpenAI Codex and Other Large Language Models Help Us Fix Security Bugs?
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Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training
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UMLAUT: Debugging Deep Learning Programs using Program Structure and Model Behavior. In CHI ’21: CHI Conference on Human Factors in Computing Systems, Virtual Event / Yokohama, Japan, May 8-13, 2021 , Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, Takeo Igarashi, Pernille Bjørn, et al
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DeepLocalize: Fault Localization for Deep Neural Networks. In ICSE’21: The 43nd International Conference on Software Engineering
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AUTOTRAINER: An Automatic DNN Training Problem Detection and Repair System. In ICSE’21: The 43nd International Conference on Software Engineering
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DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs. In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22) . Association for Computing Machinery, New York, NY, USA, 573–585
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How Well Does ChatGPT Do When Taking the Medical Licensing Exams? The Implications of Large Language Models for Medical Education and Knowledge Assessment
Aidan Gilson, Conrad Safranek, Thomas Huang, Vimig Socrates, Ling Chi, et al · 2022
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Tomasz Korbak, Hady Elsahar, Germán Kruszewski, and Marc Dymetman. 2022 · 2022
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Training language models to follow instructions with human feedback
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Synchromesh: Reliable Code Generation from Pre-trained Language Models. In International Conference on Learning Representations (ICLR ’22)
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Mathematical capabilities of chatgpt
Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, et al · 2023
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ChatGPT is not all you need. A State of the Art Review of large Generative AI models
Roberto Gozalo-Brizuela and Eduardo C Garrido-Merchan. 2023 · 2023
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http://grammarly.com
Grammarly. Accessed: 2023 · 2023
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How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
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Impact of Code Language Models on Automated Program Repair. In Proceedings of the 45th International Conference on Software Engineering (ICSE ’23)
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Effect of scale on catastrophic forgetting in neural networks. In International Conference on Learning Representations
Vinay Venkatesh Ramasesh, Aitor Lewkowycz, and Ethan Dyer. 2022 · 2022
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DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs. In Proceedings of the 44th International Conference on Software Engineering (ICSE ’22) . Association for Computing Machinery, New York, NY, USA, 561–572
Mohammad Wardat, Breno Dantas Cruz, Wei Le, and Hridesh Rajan. 2022 · 2022
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Practical Program Repair in the Era of Large Pre-trained Language Models
Chun Xia, Yuxiang Wei, and Lingming Zhang. 2022 · 2022
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An Extensive Study on Pre-Trained Models for Program Understanding and Generation. In Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022) . Association for Computing Machinery, New York, NY, USA, 39–51
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https://stackoverflow.com/questions/48221692
Create a square function estimator with Keras. Accessed: 2023 · 2023
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Few-Shot Training LLMs for Project-Specific Code-Summarization. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE ’22) . Association for Computing Machinery, New York, NY, USA, Article 177, 5 pages
Toufique Ahmed and Premkumar Devanbu. 2023 · 2023
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Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, et al · 2023
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Very basic Keras CNN with 2 classes giving inexplicable answers. Accessed: 2023 · 2023
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https://stackoverflow.com/questions/45442843
Sigmoid layer in Keras. Accessed: 2023 · 2023
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Pre-Train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, et al · 2023
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Keras model to fit polynomial. Accessed: 2023 · 2023
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Retrieval-Based Prompt Selection for Code-Related Few-Shot Learning. In Proceedings of the 45th International Conference on Software Engineering (ICSE ’23)
Noor Nashid, Mifta Sintaha, and Ali Mesbah. 2023 · 2023
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https://stackoverflow.com/questions/50306988
Neural net fails on toy dataset. Accessed: 2023 · 2023
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https://stackoverflow.com/questions/39525358
Neural network accuracy optimization. Accessed: 2023 · 2023
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An analysis of the automatic bug fixing performance of chatgpt
Dominik Sobania, Martin Briesch, Carol Hanna, and Justyna Petke. 2023 · 2023
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https://stackoverflow.com/questions/55328966
tf.keras loss becomes NaN. Accessed: 2023 · 2023
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https://stackoverflow.com/questions/33969059
Trying to get simple Keras neural net example to work. Accessed: 2023 · 2023
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https://stackoverflow.com/questions/31556268
How to use keras for XOR. Accessed: 2023 · 2023
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https://stackoverflow.com/questions/31627380
Trying Kaggle Titanic with keras .. getting loss and valid_loss 0.0000. Accessed: 2023 · 2023
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