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Found 4 papers, 4 papers with code
JumpCoder: Go Beyond Autoregressive Coder via Online Modification
While existing code large language models (code LLMs) exhibit impressive capabilities in code generation, their autoregressive sequential generation inherently lacks reversibility.
CCRep: Learning Code Change Representations via Pre-Trained Code Model and Query Back
To fill this gap, this work proposes a novel Code Change Representation learning approach named CCRep, which can learn to encode code changes as feature vectors for diverse downstream tasks.
Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural Network
Considering the lack of technologies in Plot2API, we present a novel deep multi-task learning approach named Semantic Parsing Guided Neural Network (SPGNN) which translates the Plot2API issue as a multi-label image classification and an image semantic parsing tasks for the solution.
Automatic Generation of Pull Request Descriptions
We build a dataset with over 41K PRs and evaluate our approach on this dataset through ROUGE and a human evaluation.
Software Engineering
