Software engineering is a domain characterized by intricate decision-making processes,
often relying on nuanced intuition and consultation. Recent advancements in deep learning …

Software development is a complex task that necessitates cooperation among multiple
members with diverse skills. Numerous studies used deep learning to improve specific …

The contemporary LLMs are prone to producing hallucinations, stemming mainly from the
knowledge gaps within the models. To address this critical limitation, researchers employ …

Various human-designed prompt engineering techniques have been proposed to improve
problem solvers based on Large Language Models (LLMs), yielding many disparate code …

Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …

To enhance the reasoning capabilities of off-the-shelf Large Language Models (LLMs), we
introduce a simple, yet general and effective prompting method, RE2, ie, Re-Reading the …

Recent studies show that collaborating multiple large language model (LLM) powered
agents is a promising way for task solving. However, current approaches are constrained by …

Reinforcement learning (RL) has been widely used in training large language
models~(LLMs) for preventing unexpected outputs,\eg reducing harmfulness and errors …

Abstract Machine reasoning, which involves solving complex problems through step-by-step
deduction and analysis, is a crucial indicator of the capabilities of Large Language Models …

Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …