Although large language models (LLMs) have demonstrated remarkable code-generation
ability, they still struggle with complex tasks. In real-world software development, humans …

Conventional state representations in reinforcement learning often omit critical task-related
details, presenting a significant challenge for value networks in establishing accurate …

Finding appropriate prompts for the specific task has become an important issue as the
usage of Large Language Models (LLM) has expanded. Reinforcement Learning (RL) is …

This study examines the effect of prompt engineering on the performance of Large
Language Models (LLMs) in clinical note generation. We introduce an Automatic Prompt …

Recently, multimodal large language models (MLLMs) have demonstrated strong visual
understanding and decision-making capabilities, enabling the exploration of autonomously …

Inspired by human cognitive behavior, we introduce visual modality to enhance the
performance of pure text-based question-answering tasks with the development of …

This study examines the effect of prompt engineering on the performance of Large
Language Models (LLMs) in clinical note generation. We introduce an Automatic Prompt …

Large Language Models offer new opportunities to devise automated implementation
generation methods that can tackle problem solving activities beyond traditional methods …

This study introduces a novel integration of a Probabilistic Inference Layer (PIL) into the
Mistral Large Language Model (LLM), aiming to address the critical challenge of accurate …