SEVA trains a verification agent with a decomposed process reward to produce structured fact attributions, enabling a self-evolution loop that matches GPT-4o-mini F1 on ClearFacts while generating richer output.
MARCH: Multi-agent reinforced self-check for LLM hallucination
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SEVA: Self-Evolving Verification Agent with Process Reward for Fact Attribution
SEVA trains a verification agent with a decomposed process reward to produce structured fact attributions, enabling a self-evolution loop that matches GPT-4o-mini F1 on ClearFacts while generating richer output.