An LLM-based review system processing 290 real submissions was far faster and cheaper than human review, yet agreed with the conference's acceptance decisions only 38.6% of the time, indicating LLMs should assist rather than replace human reviewers.
On protecting the data privacy of large language models (llms) and llm agents: A literature review,
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Can Large Language Models Be Trusted Paper Reviewers? A Feasibility Study
An LLM-based review system processing 290 real submissions was far faster and cheaper than human review, yet agreed with the conference's acceptance decisions only 38.6% of the time, indicating LLMs should assist rather than replace human reviewers.