This paper explores the potential of Large Language Models (LLMs), specifically GPT-4, to
enhance the precision and effectiveness of Automated Assessment Systems (AAS) for open …

The development of large language models (LLMs) brings significant changes to the field of
natural language processing (NLP), enabling remarkable performance in various high-level …

This study unveils the In-Context Evolutionary Search (ICE-SEARCH) method, which is
among the first works that melds large language models (LLMs) with evolutionary algorithms …

Cross-lingual chain-of-thought can effectively complete reasoning tasks across languages,
which gains increasing attention. Recently, dominant approaches in the literature improve …

Curriculum Learning (CL) is emerging as a relevant technique to reduce the cost of pre-
training Large Language Models. The idea, tested for the English language, is to train LLMs …

Abstract Instruction-tuned Large Language Models (It-LLMs) are changing NLP thanks to
their easy accessibility. These models seem able to grasp language, solve complex tasks …

Earlier works have been showing the efficacy of reasoning methods in eliciting step-wise
reasoning of large language models (LLMs) by operating via in-context demonstrations …

In this paper, we introduce DeAR (_Decompose-Analyze-Rethink_), a framework that
iteratively builds a reasoning tree to tackle intricate problems within a single large language …