deploy: d188b54

mallamanis · mallamanis · commit 38ae77ecde61 · 2023-04-24T13:21:18.000Z
diff --git a/index.html b/index.html
@@ -119,7 +119,6 @@ <h3 id="machine-learning-on-source-code">Machine Learning on Source Code</h3>
 
 <h4 id="-browse-papers-by-tag">🏷 Browse Papers by Tag</h4>
 
-<tag><a href="/tags.html#Adapters">Adapters</a></tag>
 <tag><a href="/tags.html#adversarial">adversarial</a></tag>
 <tag><a href="/tags.html#API">API</a></tag>
 <tag><a href="/tags.html#autocomplete">autocomplete</a></tag>
@@ -128,9 +127,7 @@ <h4 id="-browse-papers-by-tag">🏷 Browse Papers by Tag</h4>
 <tag><a href="/tags.html#clone">clone</a></tag>
 <tag><a href="/tags.html#code completion">code completion</a></tag>
 <tag><a href="/tags.html#code generation">code generation</a></tag>
-<tag><a href="/tags.html#Code Refinement">Code Refinement</a></tag>
 <tag><a href="/tags.html#code similarity">code similarity</a></tag>
-<tag><a href="/tags.html#Code Summarization">Code Summarization</a></tag>
 <tag><a href="/tags.html#compilation">compilation</a></tag>
 <tag><a href="/tags.html#dataset">dataset</a></tag>
 <tag><a href="/tags.html#decompilation">decompilation</a></tag>
@@ -157,7 +154,6 @@ <h4 id="-browse-papers-by-tag">🏷 Browse Papers by Tag</h4>
 <tag><a href="/tags.html#naming">naming</a></tag>
 <tag><a href="/tags.html#optimization">optimization</a></tag>
 <tag><a href="/tags.html#pattern mining">pattern mining</a></tag>
-<tag><a href="/tags.html#Pre-trained Programming Language">Pre-trained Programming Language</a></tag>
 <tag><a href="/tags.html#pretraining">pretraining</a></tag>
 <tag><a href="/tags.html#program analysis">program analysis</a></tag>
 <tag><a href="/tags.html#refactoring">refactoring</a></tag>
diff --git a/paper-abstracts.json b/paper-abstracts.json
diff --git a/papers.html b/papers.html
diff --git a/publications-metadata/ahmad2020transformer.json b/publications-metadata/ahmad2020transformer.json
@@ -1 +1 @@
-[["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["haque2020improved", "Improved Automatic Summarization of Subroutines via Attention to File Context"], ["ye2020leveraging", "Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning"], ["shido2019automatic", "Automatic Source Code Summarization with Extended Tree-LSTM"]]
+[["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["haque2020improved", "Improved Automatic Summarization of Subroutines via Attention to File Context"], ["ye2020leveraging", "Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning"], ["fernandes2019structured", "Structured Neural Summarization"]]
diff --git a/publications-metadata/allamanis2021self.json b/publications-metadata/allamanis2021self.json
@@ -1 +1 @@
-[["pradel2017deep", "Deep Learning to Find Bugs"], ["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"], ["wang2020learning", "Learning Semantic Program Embeddings with Graph Interval Neural Network"]]
+[["pradel2017deep", "Deep Learning to Find Bugs"], ["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["wang2020learning", "Learning Semantic Program Embeddings with Graph Interval Neural Network"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"]]
diff --git a/publications-metadata/chen2021evaluating.json b/publications-metadata/chen2021evaluating.json
@@ -1 +1 @@
-[["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"]]
+[["jesse2023large", "Large Language Models and Simple, Stupid Bugs"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"]]
diff --git a/publications-metadata/devlin2017semantic.json b/publications-metadata/devlin2017semantic.json
@@ -1 +1 @@
-[["vasic2019neural", "Neural Program Repair by Jointly Learning to Localize and Repair"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"], ["ye2021neural", "Neural Program Repair with Execution-based Backpropagation"], ["allamanis2021self", "Self-Supervised Bug Detection and Repair"]]
+[["vasic2019neural", "Neural Program Repair by Jointly Learning to Localize and Repair"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"], ["ye2021neural", "Neural Program Repair with Execution-based Backpropagation"], ["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"]]
diff --git a/publications-metadata/haque2020improved.json b/publications-metadata/haque2020improved.json
@@ -1 +1 @@
-[["allamanis2016convolutional", "A Convolutional Attention Network for Extreme Summarization of Source Code"], ["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["iyer2016summarizing", "Summarizing Source Code using a Neural Attention Model"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"]]
+[["allamanis2016convolutional", "A Convolutional Attention Network for Extreme Summarization of Source Code"], ["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"], ["iyer2016summarizing", "Summarizing Source Code using a Neural Attention Model"]]
diff --git a/publications-metadata/hong2021fix.json b/publications-metadata/hong2021fix.json
@@ -1 +1 @@
-[["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["berabi2021tfix", "TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"]]
+[["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["berabi2021tfix", "TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"]]
diff --git a/publications-metadata/jesse2023large.json b/publications-metadata/jesse2023large.json
@@ -0,0 +1 @@
+[["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["chen2021evaluating", "Evaluating Large Language Models Trained on Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"]]
diff --git a/publications-metadata/lee2020montage.json b/publications-metadata/lee2020montage.json
@@ -1 +1 @@
-[["tran2019recovering", "Recovering Variable Names for Minified Code with Usage Contexts"], ["patra2016learning", "Learning to Fuzz: Application-Independent Fuzz Testing with Probabilistic, Generative Models of Input Data"], ["russell2018automated", "Automated Vulnerability Detection in Source Code Using Deep Representation Learning"], ["chakraborty2020deep", "Deep Learning based Vulnerability Detection: Are We There Yet?"]]
+[["tran2019recovering", "Recovering Variable Names for Minified Code with Usage Contexts"], ["patra2016learning", "Learning to Fuzz: Application-Independent Fuzz Testing with Probabilistic, Generative Models of Input Data"], ["russell2018automated", "Automated Vulnerability Detection in Source Code Using Deep Representation Learning"], ["he2019learning", "Learning to Fuzz from Symbolic Execution with Application to Smart Contracts"]]
diff --git a/publications-metadata/lu2022reacc.json b/publications-metadata/lu2022reacc.json
@@ -1 +1 @@
-[["popov2021time", "Time-Efficient Code Completion Model for the R Programming Language"], ["li2021toward", "Toward Less Hidden Cost of Code Completion with Acceptance and Ranking Models"], ["guo2022learning", "Learning to Complete Code with Sketches"], ["bruch2009learning", "Learning from Examples to Improve Code Completion Systems"]]
+[["li2021toward", "Toward Less Hidden Cost of Code Completion with Acceptance and Ranking Models"], ["popov2021time", "Time-Efficient Code Completion Model for the R Programming Language"], ["guo2022learning", "Learning to Complete Code with Sketches"], ["bruch2009learning", "Learning from Examples to Improve Code Completion Systems"]]
diff --git a/publications-metadata/mangal2015user.json b/publications-metadata/mangal2015user.json
@@ -1 +1 @@
-[["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["raghothaman2018user", "User-guided program reasoning using Bayesian inference"], ["wang2016bugram", "Bugram: bug detection with n-gram language models"], ["poesia2022synchromesh", "Synchromesh: Reliable code generation from pre-trained language models"]]
+[["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["wang2016bugram", "Bugram: bug detection with n-gram language models"], ["raghothaman2018user", "User-guided program reasoning using Bayesian inference"], ["poesia2022synchromesh", "Synchromesh: Reliable code generation from pre-trained language models"]]
diff --git a/publications-metadata/mukherjee2020searching.json b/publications-metadata/mukherjee2020searching.json
@@ -1 +1 @@
-[["nadeem2022codedsi", "CodeDSI: Differentiable Code Search"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"], ["li2019neural", "Neural Code Search Evaluation Dataset"], ["luan2019aroma", "Aroma: code recommendation via structural code search"]]
+[["nadeem2022codedsi", "CodeDSI: Differentiable Code Search"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"], ["li2019neural", "Neural Code Search Evaluation Dataset"], ["clement2021distilling", "Distilling Transformers for Neural Cross-Domain Search"]]
diff --git a/publications-metadata/mukherjee2021neural.json b/publications-metadata/mukherjee2021neural.json
@@ -1 +1 @@
-[["nijkamp2022conversational", "A Conversational Paradigm for Program Synthesis"], ["ling2016latent", "Latent Predictor Networks for Code Generation"], ["xu2019method", "Method name suggestion with hierarchical attention networks"], ["loyola2018content", "Content Aware Source Code Change Description Generation"]]
+[["nijkamp2022conversational", "A Conversational Paradigm for Program Synthesis"], ["xu2019method", "Method name suggestion with hierarchical attention networks"], ["loyola2018content", "Content Aware Source Code Change Description Generation"], ["ling2016latent", "Latent Predictor Networks for Code Generation"]]
diff --git a/publications-metadata/pearce2021empirical.json b/publications-metadata/pearce2021empirical.json
@@ -1 +1 @@
-[["vaithilingam2022expectation", "Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models"], ["barke2022grounded", "Grounded Copilot: How Programmers Interact with Code-Generating Models"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"]]
+[["vaithilingam2022expectation", "Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models"], ["barke2022grounded", "Grounded Copilot: How Programmers Interact with Code-Generating Models"], ["jesse2023large", "Large Language Models and Simple, Stupid Bugs"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"]]
diff --git a/publications-metadata/richter2022can.json b/publications-metadata/richter2022can.json
@@ -1 +1 @@
-[["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"], ["he2022distribution", "On Distribution Shift in Learning-based Bug Detectors"]]
+[["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["he2022distribution", "On Distribution Shift in Learning-based Bug Detectors"], ["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"]]
diff --git a/publications-metadata/shrivastava2020repository.json b/publications-metadata/shrivastava2020repository.json
@@ -1 +1 @@
-[["ahmed2033improving", "Improving Few-Shot Prompts with Relevant Static Analysis Products"], ["mangal2015user", "A User-Guided Approach to Program Analysis"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"]]
+[["jesse2023large", "Large Language Models and Simple, Stupid Bugs"], ["ahmed2033improving", "Improving Few-Shot Prompts with Relevant Static Analysis Products"], ["mangal2015user", "A User-Guided Approach to Program Analysis"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"]]
diff --git a/publications-metadata/spirin2021psiminer.json b/publications-metadata/spirin2021psiminer.json
@@ -1 +1 @@
-[["shido2019automatic", "Automatic Source Code Summarization with Extended Tree-LSTM"], ["zhang2019novel", "A Novel Neural Source Code Representation based on Abstract Syntax Tree"], ["rabinovich2017abstract", "Abstract Syntax Networks for Code Generation and Semantic Parsing"], ["wang2020modular", "Modular Tree Network for Source Code Representation Learning"]]
+[["zhang2019novel", "A Novel Neural Source Code Representation based on Abstract Syntax Tree"], ["shido2019automatic", "Automatic Source Code Summarization with Extended Tree-LSTM"], ["rabinovich2017abstract", "Abstract Syntax Networks for Code Generation and Semantic Parsing"], ["wang2020modular", "Modular Tree Network for Source Code Representation Learning"]]
diff --git a/publications-metadata/tabassum2020code.json b/publications-metadata/tabassum2020code.json
@@ -1 +1 @@
-[["parvez2018building", "Building Language Models for Text with Named Entities"], ["sharma2022lamner", "LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition"], ["sharma2022exploratory", "An Exploratory Study on Code Attention in BERT"], ["sharma2015nirmal", "NIRMAL: Automatic Identification of Software Relevant Tweets Leveraging Language Model"]]
+[["parvez2018building", "Building Language Models for Text with Named Entities"], ["sharma2022lamner", "LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition"], ["sharma2022exploratory", "An Exploratory Study on Code Attention in BERT"], ["saberi2023model", "Model-Agnostic Syntactical Information for Pre-Trained Programming Language Models"]]
diff --git a/publications-metadata/waunakh2019idbench.json b/publications-metadata/waunakh2019idbench.json
@@ -1 +1 @@
-[["yonai2019mercem", "Mercem: Method Name Recommendation Based on Call Graph Embedding"], ["alon2019code2vec", "code2vec: Learning Distributed Representations of Code"], ["tufano2018deep", "Deep Learning Similarities from Different Representations of Source Code"], ["jian2021multimodal", "Multimodal Representation for Neural Code Search"]]
+[["yonai2019mercem", "Mercem: Method Name Recommendation Based on Call Graph Embedding"], ["alon2019code2vec", "code2vec: Learning Distributed Representations of Code"], ["jian2021multimodal", "Multimodal Representation for Neural Code Search"], ["tufano2018deep", "Deep Learning Similarities from Different Representations of Source Code"]]
diff --git a/publications-metadata/xu2022systematic.json b/publications-metadata/xu2022systematic.json
@@ -1 +1 @@
-[["chen2021evaluating", "Evaluating Large Language Models Trained on Code"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"], ["sarkar2022what", "What is it like to program with artificial intelligence?"]]
+[["jesse2023large", "Large Language Models and Simple, Stupid Bugs"], ["chen2021evaluating", "Evaluating Large Language Models Trained on Code"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"]]
diff --git a/publications-metadata/zhou2019devign.json b/publications-metadata/zhou2019devign.json
@@ -1 +1 @@
-[["chen2023diversevul", "DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection"], ["russell2018automated", "Automated Vulnerability Detection in Source Code Using Deep Representation Learning"], ["abdelaziz2020graph4code", "Graph4Code: A Machine Interpretable Knowledge Graph for Code"], ["chakraborty2020deep", "Deep Learning based Vulnerability Detection: Are We There Yet?"]]
+[["chen2023diversevul", "DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection"], ["russell2018automated", "Automated Vulnerability Detection in Source Code Using Deep Representation Learning"], ["abdelaziz2020graph4code", "Graph4Code: A Machine Interpretable Knowledge Graph for Code"], ["nair2020funcgnn", "funcGNN: A Graph Neural Network Approach to Program Similarity"]]
diff --git a/publications-metadata/zhou2021improving.json b/publications-metadata/zhou2021improving.json
@@ -1 +1 @@
-[["aye2020learning", "Learning Autocompletion from Real-World Datasets"], ["popov2021time", "Time-Efficient Code Completion Model for the R Programming Language"], ["ahmed2022learning", "Learning code summarization from a small and local dataset"], ["schuster2021you", "You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion"]]
+[["aye2020learning", "Learning Autocompletion from Real-World Datasets"], ["popov2021time", "Time-Efficient Code Completion Model for the R Programming Language"], ["schuster2021you", "You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion"], ["ahmed2022learning", "Learning code summarization from a small and local dataset"]]
diff --git a/publications-metadata/zhou2022codebertscore.json b/publications-metadata/zhou2022codebertscore.json
@@ -1 +1 @@
-[["eghbali2022crystalbleu", "CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code"], ["chen2022codet", "CodeT: Code Generation with Generated Tests"], ["ren2020codebleu", "CodeBLEU: a Method for Automatic Evaluation of Code Synthesis"], ["haque2022semantic", "Semantic Similarity Metrics for Evaluating Source Code Summarization"]]
+[["eghbali2022crystalbleu", "CrystalBLEU: Precisely and Efficiently Measuring the Similarity of Code"], ["ren2020codebleu", "CodeBLEU: a Method for Automatic Evaluation of Code Synthesis"], ["chen2022codet", "CodeT: Code Generation with Generated Tests"], ["haque2022semantic", "Semantic Similarity Metrics for Evaluating Source Code Summarization"]]
diff --git a/publications/jesse2023large/index.html b/publications/jesse2023large/index.html
diff --git a/publications/saberi2023model/index.html b/publications/saberi2023model/index.html
diff --git a/tags.html b/tags.html
diff --git a/topics.json b/topics.json
diff --git a/tsne.json b/tsne.json

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`1`		`-[["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["haque2020improved", "Improved Automatic Summarization of Subroutines via Attention to File Context"], ["ye2020leveraging", "Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning"], ["shido2019automatic", "Automatic Source Code Summarization with Extended Tree-LSTM"]]`
	`1`	`+[["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["haque2020improved", "Improved Automatic Summarization of Subroutines via Attention to File Context"], ["ye2020leveraging", "Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning"], ["fernandes2019structured", "Structured Neural Summarization"]]`
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`1`		`-[["pradel2017deep", "Deep Learning to Find Bugs"], ["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"], ["wang2020learning", "Learning Semantic Program Embeddings with Graph Interval Neural Network"]]`
	`1`	`+[["pradel2017deep", "Deep Learning to Find Bugs"], ["patra2021semantic", "A Semantic Bug Seeding: A Learning-Based Approach for Creating Realistic Bugs"], ["wang2020learning", "Learning Semantic Program Embeddings with Graph Interval Neural Network"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"]]`
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`1`		`-[["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["doderlein2022piloting", "Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?"]]`
	`1`	`+[["jesse2023large", "Large Language Models and Simple, Stupid Bugs"], ["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"]]`
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`1`		`-[["vasic2019neural", "Neural Program Repair by Jointly Learning to Localize and Repair"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"], ["ye2021neural", "Neural Program Repair with Execution-based Backpropagation"], ["allamanis2021self", "Self-Supervised Bug Detection and Repair"]]`
	`1`	`+[["vasic2019neural", "Neural Program Repair by Jointly Learning to Localize and Repair"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"], ["ye2021neural", "Neural Program Repair with Execution-based Backpropagation"], ["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"]]`
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`1`		`-[["allamanis2016convolutional", "A Convolutional Attention Network for Extreme Summarization of Source Code"], ["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["iyer2016summarizing", "Summarizing Source Code using a Neural Attention Model"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"]]`
	`1`	`+[["allamanis2016convolutional", "A Convolutional Attention Network for Extreme Summarization of Source Code"], ["wang2020cocogum", "CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs"], ["parvez2021retrieval", "Retrieval Augmented Code Generation and Summarization"], ["iyer2016summarizing", "Summarizing Source Code using a Neural Attention Model"]]`
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`1`		`-[["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["berabi2021tfix", "TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer"], ["richter2022can", "Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes"]]`
	`1`	`+[["hata2018learning", "Learning to Generate Corrective Patches using Neural Machine Translation"], ["dinella2020hoppity", "Hoppity: Learning Bug Detection and Repair"], ["berabi2021tfix", "TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer"], ["chen2019sequencer", "SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair"]]`
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	`1`	`+[["xu2022systematic", "A Systematic Evaluation of Large Language Models of Code"], ["shrivastava2020repository", "Repository-Level Prompt Generation for Large Language Models of Code"], ["chen2021evaluating", "Evaluating Large Language Models Trained on Code"], ["pearce2021empirical", "An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions"]]`