3 citations · 9 across the 35 of their papers we have counts for
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q-fin.PM2024★ 3 cited
Automate Strategy Finding with LLM in Quant Investment
Zhizhuo Kou, Holam Yu, Junyu Luo +7
We present a novel three-stage framework leveraging Large Language Models (LLMs) within a risk-aware multi-agent system for automate strategy finding in quantitative finance. Our a…
cs.AI2024★ 2 cited
PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference
Jiaming Ji, Donghai Hong, Borong Zhang +10
In this study, we introduce the safety human preference dataset, PKU-SafeRLHF, designed to promote research on safety alignment in large language models (LLMs). As a sibling projec…