Hallucination Mitigation

Tencent Cloud Developer

Apr 2, 2025 · Artificial Intelligence

Understanding Retrieval‑Augmented Generation (RAG): Concepts, Types, and Development

Retrieval‑Augmented Generation (RAG) enhances large language models by fetching up‑to‑date external knowledge before generation, mitigating knowledge‑cutoff limits and hallucinations through a retrieval step (using text, vector, or graph methods) and a generation step, evolving from naive single‑method approaches to advanced, modular, graph‑based, and agentic systems that enable adaptive, multi‑hop reasoning and future intelligent, multimodal pipelines.

AIAgentic AIHallucination Mitigation

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Understanding Retrieval‑Augmented Generation (RAG): Concepts, Types, and Development

AntTech

Mar 18, 2025 · Artificial Intelligence

MoLE: Decoding by Mixture of Layer Experts Alleviates Hallucination in Large Vision-Language Models

Researchers from Ant Insurance and Zhejiang University propose MoLE, a Mixture of Layer Experts decoding method that reduces hallucinations in large vision‑language models, demonstrating state‑of‑the‑art performance on LVLM benchmarks and enabling reliable end‑to‑end medical‑record‑to‑claim automation.

AIHallucination MitigationInsurance Automation

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MoLE: Decoding by Mixture of Layer Experts Alleviates Hallucination in Large Vision-Language Models