Let Me Teach You: Pedagogical Foundations of Feedback for Language
  Models
Beatriz Borges Niket Tandon Tanja Käser Antoine Bosselut
Natural Language Feedback (NLF) is an increasingly popular avenue to align
Large Language Models (LLMs) to human preferences. Despite the richness and
diversity of the information it can convey, NLF is often hand-designed and
arbitrary. In a different world, research in pedagogy has long established
several effective feedback models. In this opinion piece, we compile ideas from
pedagogy to introduce FELT, a feedback framework for LLMs that outlines the
various characteristics of the feedback space, and a feedback content taxonomy
based on these variables. Our taxonomy offers both a general mapping of the
feedback space, as well as pedagogy-established discrete categories, allowing
us to empirically demonstrate the impact of different feedback types on revised
generations. In addition to streamlining existing NLF designs, FELT also brings
out new, unexplored directions for research in NLF. We make our taxonomy
available to the community, providing guides and examples for mapping our
categorizations to future resources.