Teaching a black-box learner

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Self-Refine: Iterative Refinement with Self-Feedback (2023, background): “Non-NL feedback can come in human-provided example pairs (Dasgupta et al., 2019) or dense signals (Liu et al.”
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing (2023, background): “There are two main forms of feedback: scalar signals (Dasgupta et al., 2019) are commonly used for reinforcement learning (Ziegler et al.”
A Competence-aware Curriculum for Visual Concepts Learning via Question Answering (2020, background): “the diculty of each question. 2.2 Curriculum Learning and Machine Teaching The competence-aware curriculum in our work is related to curriculum learning [7,54,56,20,51,45,21,48] and machine teaching [61,62,39,11,41,15,58]. Curriculum learning is rstly proposed by Bengio et al. [7] and demonstrates t”
Interscript: A dataset for interactive learning of scripts through error feedback (2021, methodology): “Finally, the model being taught is treated either as (i) a black box (as in machine teaching (Dasgupta et al. 2019; Talmor et al. 2020)) or (ii) the beliefs of the model are in some form exposed to feedback (as in interactive semantic parsing (Elgohary et al. 2021)).”