5 papers
Greedy Decoding Is Not Precision-Invariant: Cross-Precision Output Divergence in LLM Inference
Gaoyuan Du, Anam Nawaz Khan, Rex Zhou +4
Greedy decoding from large language models is commonly treated as deterministic. We show it is not precision-invariant: the same model, prompt, and decoding algorithm produce diffe…
When Does Context Routing Help? A Systematic Study of Multi-Modal Fusion in Time Series Forecasting
Ruizhe Zhou, Gaoyuan Du, Xiaoyang Liu +4
Multi-modal time series forecasting methods integrate auxiliary context into temporal predictions through increasingly sophisticated fusion mechanisms. A growing body of work repor…
From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems
Ruizhe Zhou, Xiaoyang Liu, Gaoyuan Du +4
Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabilities in algorithmic reprodu…
zkFinGPT: Zero-Knowledge Proofs for Financial Generative Pre-trained Transformers
Xiao-Yang Liu, Ningjie Li, Keyi Wang +2
Financial Generative Pre-trained Transformers (FinGPT) with multimodal capabilities are now being increasingly adopted in various financial applications. However, due to the intell…
Reasoning Models Ace the CFA Exams
Jaisal Patel, Yunzhe Chen, Kaiwen He +4
Previous research has reported that large language models (LLMs) demonstrate poor performance on the Chartered Financial Analyst (CFA) exams. However, recent reasoning models have…