3 papers
cs.CL2024
Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?
Haohan Zhang, Fengrui Hua, Chengjin Xu +3
The rapid advancement of Large Language Models (LLMs) has spurred discussions about their potential to enhance quantitative trading strategies. LLMs excel in analyzing sentiments a…
cs.CL2024
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang +6
Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep an…
cs.CL2024
Ensuring Safe and High-Quality Outputs: A Guideline Library Approach for Language Models
Yi Luo, Zhenghao Lin, Yuhao Zhang +7
Large Language Models (LLMs) exhibit impressive capabilities but also present risks such as biased content generation and privacy issues. One of the current alignment techniques in…