3 accepted papers
In the post-Turing era, evaluating large language models (LLMs) involves assessing generated text based on readers’ decisions rather than merely its indistinguishability from human-produced content. This paper explores how LLM-generated text impacts readers’ decisions, focusing on both amateur and e…
The generation of synthetic financial data is a critical technology in the financial domain, addressing challenges posed by limited data availability. Traditionally, statistical models have been employed to generate synthetic data. However, these models fail to capture the stylized facts commonly ob
Recently, Large Language Models (LLMs) have attracted significant attention for their exceptional performance across a broad range of tasks, particularly in text analysis. However, the finance sector presents a distinct challenge due to its dependence on time-series data for complex forecasting task…