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Distilled GPT for source code summarization
International Conference on Automated Software Engineering, 2023A code summary is a brief natural language description of source code. Summaries are usually only a single sentence long, and yet form the backbone of developer documentation.
Chia-Yi Su, Collin McMillan
semanticscholar +1 more source
SPT-Code: Sequence-to-Sequence Pre-Training for Learning Source Code Representations
International Conference on Software Engineering, 2022Recent years have seen the successful application of large pretrained models to code representation learning, resulting in substantial improvements on many code-related downstream tasks.
Changan Niu +5 more
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What Do They Capture? - A Structural Analysis of Pre-Trained Language Models for Source Code
International Conference on Software Engineering, 2022Recently, many pre-trained language models for source code have been proposed to model the context of code and serve as a basis for downstream code intelligence tasks such as code completion, code search, and code summarization.
Yao Wan +5 more
semanticscholar +1 more source
IEEE Transactions on Information Theory, 2015
Emerging applications including semantic information processing impose priorities on the possible realizations of information sources, so that not all source sequences are important. This paper proposes an initial framework for optimal lossless compression of subsets of the output of a discrete memoryless source (DMS).
Ebrahim MolavianJazi, Aylin Yener
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Emerging applications including semantic information processing impose priorities on the possible realizations of information sources, so that not all source sequences are important. This paper proposes an initial framework for optimal lossless compression of subsets of the output of a discrete memoryless source (DMS).
Ebrahim MolavianJazi, Aylin Yener
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Source coding for dependent sources
2012 IEEE Information Theory Workshop, 2012In this work, we address the capacity region of multi-source multi-terminal network communication problems, and study the change in capacity when one moves form independent to dependent source information. Specifically, we ask whether the trade off between capacity and source independence is of continuous nature.
Michael Langberg, Michelle Effros
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Lossless source coding with polar codes
2010 IEEE International Symposium on Information Theory, 2010In this paper lossless compression with polar codes is considered. A polar encoding algorithm is developed and a method to design the code and compute the average compression rate for finite lengths is given. It is shown that the scheme achieves the optimal compression rate asymptotically. Furthermore, the proposed scheme has a very good performance at
HarmS. Cronie, Satish Babu Korada
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A Novel Neural Source Code Representation Based on Abstract Syntax Tree
International Conference on Software Engineering, 2019Exploiting machine learning techniques for analyzing programs has attracted much attention. One key problem is how to represent code fragments well for follow-up analysis.
Jian Zhang +5 more
semanticscholar +1 more source
Retrieval-based Neural Source Code Summarization
International Conference on Software Engineering, 2020Source code summarization aims to automatically generate concise summaries of source code in natural language texts, in order to help developers better understand and maintain source code.
Jian Zhang +4 more
semanticscholar +1 more source
2011 IEEE International Symposium on Information Theory Proceedings, 2011
A coding problem, over a slotted system, is introduced where the sender has to transmit one out of several packets to the receiver, but learns the request only at the beginning of each slot with prior statistical information about which packet is needed at the receiver.
Onur Güngör 0002 +3 more
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A coding problem, over a slotted system, is introduced where the sender has to transmit one out of several packets to the receiver, but learns the request only at the beginning of each slot with prior statistical information about which packet is needed at the receiver.
Onur Güngör 0002 +3 more
openaire +1 more source
IEEE Transactions on Information Theory, 1998
Summary: Lossy coding of speech, high-quality audio, still images, and video is commonplace today. However, in 1948, few lossy compression systems were in service. Shannon introduced and developed the theory of source coding with a fidelity criterion, also called rate-distortion theory.
Toby Berger, Jerry D. Gibson
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Summary: Lossy coding of speech, high-quality audio, still images, and video is commonplace today. However, in 1948, few lossy compression systems were in service. Shannon introduced and developed the theory of source coding with a fidelity criterion, also called rate-distortion theory.
Toby Berger, Jerry D. Gibson
openaire +1 more source