Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

This paper provides a comprehensive review of the current methods and metrics used to
evaluate the performance of Large Language Models (LLMs) in code generation tasks. With …

This paper introduces an innovative approach that combines Large Language Models
(LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially …

The prominent large language models (LLMs) of today differ from past language models not
only in size, but also in the fact that they are trained on a combination of natural language …

Supply chain operations traditionally involve a variety of complex decision making problems.
Over the last few decades, supply chains greatly benefited from advances in computation …

Repository-level code completion aims to generate code for unfinished code snippets within
the context of a specified repository. Existing approaches mainly rely on retrieval-augmented …

In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …

General-purpose code generation aims to automatically convert the natural language
description to code snippets in a general-purpose programming language (GPL) such as …

Deep Generative AI has been a long-standing essential topic in the machine learning
community, which can impact a number of application areas like text generation and …

The advancement of large language models (LLMs) has significantly propelled the field of
code generation. Previous work integrated reinforcement learning (RL) with compiler …