Assessment and evaluation have long been critical challenges in artificial intelligence (AI)
and natural language processing (NLP). However, traditional methods, whether matching …

Data annotation and synthesis generally refers to the labeling or generating of raw data with
relevant information, which could be used for improving the efficacy of machine learning …

Recent works have shown the benefits to LLMs from fine-tuning golden-standard Chain-of-
Thought (CoT) rationales or using them as correct examples in few-shot prompting. While …

When large language models (LLMs) exceed human-level capabilities, it becomes
increasingly challenging to provide full-scale and accurate supervision for these models …

Despite the remarkable success of Large Language Models (LLMs), evaluating their outputs'
quality regarding preference remains a critical challenge. Existing works usually leverage a …