LIMA (Less Is More for Alignment)
LIMA, short for "Less Is More for Alignment," is a 2023 research paper by Chunting Zhou and colleagues at Meta AI, Carnegie Mellon University, the University of Southern California, and Tel Aviv University…
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Self-Taught Evaluator
Self-Taught Evaluator is a method for training a strong LLM-as-a-judge without any human preference annotations, using synthetic training data and an iterative self-improvement loop.