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Reinforcement learning can efficiently merge heterogeneous language models in federated ASR, outperforming genetic algorithms and improving character error rate.
CiteLLM offers a LaTeX-integrated agent that grounds claims in trusted academic sources, bypassing LLM hallucinations by using them only for search and ranking, not content generation.
