1 citations · 1 across the 5 of their papers we have counts for
7 papers
Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?
Weixian Waylon Li, Hyeonjun Kim, Mihai Cucuringu +1
Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to generate investment decisions from unstructu…
Summoning the Oracle to Slay It: Mitigating Look-Ahead Bias in Financial Backtesting with Large Language Models
Weixian Waylon Li, Mengyu Wang, Tiejun Ma
Backtesting large language models (LLMs) on historical financial data is unreliable because pre-training cuts off after the events happened. An LLM trained in 2024 already "knows"…
Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory
Weixian Waylon Li, Jiaxin Zhang, Xianan Jim Yang +2
Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing approaches model time as discrete m…
Spectral Attention Steering for Prompt Highlighting
Weixian Waylon Li, Yuchen Niu, Yongxin Yang +3
Attention steering is an important technique for controlling model focus, enabling capabilities such as prompt highlighting, where the model prioritises user-specified text. Howeve…
Self-Improving World Modelling with Latent Actions
Yifu Qiu, Zheng Zhao, Waylon Li +4
Internal modelling of the world -- predicting transitions between previous states and next states under actions -- is essential to reasoning and planning for LLMs and V…
Learn to Rank Risky Investors: A Case Study of Predicting Retail Traders' Behaviour and Profitability
Weixian Waylon Li, Tiejun Ma
Identifying risky traders with high profits in financial markets is crucial for market makers, such as trading exchanges, to ensure effective risk management through real-time deci…