Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

While large language models (LLMs) have demonstrated remarkable capabilities across a
range of downstream tasks, a significant concern revolves around their propensity to exhibit …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Large Language Models (LLMs) have emerged as a groundbreaking technology with their
unparalleled text generation capabilities across various applications. Nevertheless …

Reinforcement learning from human feedback (RLHF) is a technique for training AI systems
to align with human goals. RLHF has emerged as the central method used to finetune state …

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

Large Language Models (LLMs) have achieved remarkable success across a wide array of
tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used …

Text evaluation has historically posed significant challenges, often demanding substantial
labor and time cost. With the emergence of large language models (LLMs), researchers …