2 citations · 3 across the 5 of their papers we have counts for
3 papers · 1 filter
Counterfactual Causal Inference in Natural Language with Large Language Models
Gaël Gendron, Jože M. Rožanec, Michael Witbrock +1
Causal structure discovery methods are commonly applied to structured data where the causal variables are known and where statistical testing can be used to assess the causal relat…
Can Large Language Models Learn Independent Causal Mechanisms?
Gaël Gendron, Bao Trung Nguyen, Alex Yuxuan Peng +2
Despite impressive performance on language modelling and complex reasoning tasks, Large Language Models (LLMs) fall short on the same tasks in uncommon settings or with distributio…
Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning
Qiming Bao, Gael Gendron, Alex Yuxuan Peng +5
Large language models (LLMs), such as LLaMA, Alpaca, Vicuna, GPT-3.5 and GPT-4, have advanced the performance of AI systems on various natural language processing tasks to human-li…