Causal Analysis of Effective Editing Strategies in Human-Language Model Collaborations

The core message of this paper is to introduce a novel causal estimand, Incremental Stylistic Effect (ISE), to evaluate the impact of various text editing strategies in dynamic human-language model collaborations, and to propose the CausalCollab algorithm to effectively estimate ISE from observational data.