Papers with 8B-parameter LLM

1 papers
MARCH: Multi-Agent Reinforced Check for Hallucination (2026.acl-long)

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Challenge: Existing methods to detect hallucinations suffer from inherent confirmation bias, where the verifier inadvertently reproduces the errors of the original generation.
Approach: They propose a framework that enforces rigorous factual alignment by leveraging deliberate *information asymmetry* by combining a pipeline of three specialized agents: a Solver, a Proposer, and a Checker.
Outcome: Extensive experiments across hallucination benchmarks demonstrate that MARCH substantially reduces hallucinism rates.

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