AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, so do risks from misalignment. To provide a comprehensive …

The rapid development of Large Language Models (LLMs) like GPT-4, Claude-3, and
Gemini has transformed the field of natural language processing. However, it has also …

Amid the expanding use of pre-training data, the phenomenon of benchmark dataset
leakage has become increasingly prominent, exacerbated by opaque training processes …

The evaluation of large language models (LLMs) is crucial to assess their performance and
mitigate potential security risks. In this paper, we introduce PromptBench, a unified library to …

Automatic evaluation methods for large language models (LLMs) are hindered by data
contamination, leading to inflated assessments of their effectiveness. Existing strategies …

The current paradigm of evaluating Large Language Models (LLMs) through static
benchmarks comes with significant limitations, such as vulnerability to data contamination …

This survey paper examines the recent advancements in AI agent implementations, with a
focus on their ability to achieve complex goals that require enhanced reasoning, planning …

Complex reasoning ability is one of the most important features of current LLMs, which has
also been leveraged to play an integral role in complex decision-making tasks. Therefore …

Evaluating and enhancing the general capabilities of large language models (LLMs) has
been an important research topic. Graph is a common data structure in the real world, and …

Pretrained language models can encode a large amount of knowledge and utilize it for
various reasoning tasks, yet they can still struggle to learn novel factual knowledge …