Abdulaal, A;
Hadjivasiliou, A;
Montaña-Brown, N;
He, T;
Ijishakin, A;
Drobnjak, I;
Castro, DC;
(2024)
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning.
In:
12th International Conference on Learning Representations, ICLR 2024.
International Conference on Learning Representations (ICLR): Vienna, Austria.
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Abstract
Scientific discovery hinges on the effective integration of metadata, which refers to a set of conceptual operations such as determining what information is relevant for inquiry, and data, which encompasses physical operations such as observation and experimentation. This paper introduces the Causal Modelling Agent (CMA), a novel framework that synergizes the metadata-based reasoning capabilities of Large Language Models (LLMs) with the data-driven modelling of Deep Structural Causal Models (DSCMs) for the task of causal discovery. We evaluate the CMA's performance on a number of benchmarks, as well as on the real-world task of modelling the clinical and radiological phenotype of Alzheimer's Disease (AD). Our experimental results indicate that the CMA can outperform previous purely data-driven or metadata-driven approaches to causal discovery. In our real-world application, we use the CMA to derive new insights into the causal relationships among biomarkers of AD.
| Type: | Proceedings paper |
|---|---|
| Title: | Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning |
| Event: | 12th International Conference on Learning Representations, ICLR 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://openreview.net/forum?id=pAoqRlTBtY |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Causal Reasoning, Causal Discovery, Structural Causal Models, Large Language Models |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10195820 |
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