most citedData-Centric Financial Large Language Models

5 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024

A Causal Explainable Guardrails for Large Language Models

Zhixuan Chu, Yan Wang, Longfei Li +3

Large Language Models (LLMs) have shown impressive performance in natural language tasks, but their outputs can exhibit undesirable attributes or biases. Existing methods for steer…

cs.CL2024★ 1 cited

Professional Agents -- Evolving Large Language Models into Autonomous Experts with Human-Level Competencies

Zhixuan Chu, Yan Wang, Feng Zhu +3

The advent of large language models (LLMs) such as ChatGPT, PaLM, and GPT-4 has catalyzed remarkable advances in natural language processing, demonstrating human-like language flue…

cs.LG2024★ 1 cited

Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction

Zhixuan Chu, Mengxuan Hu, Qing Cui +2

Since artificial intelligence has seen tremendous recent successes in many areas, it has sparked great interest in its potential for trustworthy and interpretable risk prediction.…

cs.IR2024★ 2 cited

LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation

Zhixuan Chu, Yan Wang, Qing Cui +4

As personalized recommendation systems become vital in the age of information overload, traditional methods relying solely on historical user interactions often fail to fully captu…

cs.LG2023★ 2 cited

Intelligent Virtual Assistants with LLM-based Process Automation

Yanchu Guan, Dong Wang, Zhixuan Chu +6

While intelligent virtual assistants like Siri, Alexa, and Google Assistant have become ubiquitous in modern life, they still face limitations in their ability to follow multi-step…

cs.CL2023★ 5 cited

Data-Centric Financial Large Language Models

Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou +9

Large language models (LLMs) show promise for natural language tasks but struggle when applied directly to complex domains like finance. LLMs have difficulty reasoning about and in…

cs.LG2023

Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference

Yan Wang, Zhixuan Chu, Tao Zhou +9

Asynchronous time series, also known as temporal event sequences, are the basis of many applications throughout different industries. Temporal point processes(TPPs) are the standar…