Scholar Feed

LLM reasoning / chain-of-thought

Self-Refine

Self-Refine: Iterative Refinement with Self-Feedback

Superseded baseline#9 of 772 most-superseded · first seen Mar 30, 2023

Superseded — cited as a baseline and beaten by newer methods

4 papers critique it · 3 beat it on benchmarks

What papers say

Verbatim critique sentences, each from a paper that cites Self-Refine as a baseline.

Though rewriting techniques like Self-Refine~Madaan2023SelfRefineIR can help relieve, this tendency can still lead to misleading or wrong outcomes in real-world complex mathematical problems.
— Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
“rather than relying on post-hoc reflection or global templates”
— Lateral Tree-of-Thoughts Surpasses ToT by Incorporating Logically-Consistent, Low-Utility Candidates
“In all of these methods the guidance signal---critique, scoring model, abstraction prompt---is produced by an untrained, prompted LLM.”
— Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents
“Sometimes LLMs can directly provide correct answers to questions, but after applying CoT-like methods, it brings extra reasoning paths to models, causing their answers to be wrong.”
— Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning

Beaten on benchmarks

Head-to-head results where a newer method reports beating Self-Refine. Values are copied from the source paper's tables — verify against the cited paper.

What to use instead

Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.