DLM4G applies graph-aware adaptive noising in a diffusion framework to generate text from graphs, outperforming larger autoregressive and diffusion baselines in factual grounding and edit sensitivity on three datasets plus molecule captioning.
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A multi-agent conversational system using AMA flowcharts achieves 95.29% top-3 retrieval accuracy and 99.10% navigation accuracy on large synthetic medical conversation datasets.
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