SEVA: Self-Evolving Verification Agent with Process Reward for Fact Attribution
Hallucination is the reliability bottleneck for LLM-based agents, and fact attribution verifiers are the last line of defense -- yet today's verifiers emit only opaque binary labels, leaving agents unable to self-correct and operators unable to audit. We present SEVA, a structured verification agent that emits evidence alignments, step-by-step reasoning chains, calibrated confidence, and a six-category error diagnosis with actionable fixes. Training such an agent with RL is non-trivial: standard
Record details
Published: 29 June 2026
Source: arXiv
Category: Research
Topics: Healthcare · Military & security · Agents & autonomy · Transparency
Retrieved: 14 July 2026
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ethics.ai (29 June 2026), “SEVA: Self-Evolving Verification Agent with Process Reward for Fact Attribution,” evidence record 457, https://ethics.ai/record/457 (originally published by arXiv).
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