LLM-enhanced Score Function Evolution for Causal Structure Learning
Authors: Zidong Wang, Fei Liu, Qi Feng, Qingfu Zhang, Xiaoguang Gao
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental evaluations, conducted on discrete, continuous, and real datasets, demonstrate the high stability, generality and effectiveness of L-SFE. (Abstract) |
| Researcher Affiliation | Academia | 1Department of Computer Science, City University of Hong Kong, Hong Kong 2School of Electronic and Information, Northwestern Polytechnical University, Xi an, China EMAIL, EMAIL, EMAIL, EMAIL. |
| Pseudocode | Yes | To provide a clear understanding of L-SFE, we outline the pseudo-code in Alg. 1 in Supplementary material 1.2. |
| Open Source Code | Yes | Code is avaliable on https://github.com/wzd2502/L-SFE |
| Open Datasets | Yes | synthetic datasets generated from pytetrad are employed for training and testing. For the discrete dataset... For the continuous datasets... We present a case study using data from the real world COVID-19 pandemic in the UK... https://bayesian-ai.eecs.qmul.ac.uk/bayesys/ |
| Dataset Splits | No | The paper describes generating synthetic datasets for training and testing and mentions using a real-world COVID-19 dataset with 866 samples, but does not specify explicit training/test/validation splits (e.g., percentages or counts) for a single dataset. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU models, CPU types) used for running the experiments. |
| Software Dependencies | No | The paper mentions "GPT-4o mini is utilized for score function discovery in L-SFE" and "synthetic datasets generated from pytetrad are employed", but does not provide specific version numbers for these software components. |
| Experiment Setup | Yes | For the discrete dataset, L-SFE is trained on ten Random Graphs with n = 30... Each test is repeated 10 times with m = 5000. ... The GLS used for training is HC with a tabu search. |