Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.
Knowledge graph–based thought: a knowledge graph–enhanced LLM framework for pan-cancer question answering
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A phenotype-driven framework integrates GNNs, causal inference, probabilistic reasoning, and LLMs to expand knowledge graphs via multi-objective optimization that balances novelty, relevance, and evidence validation.
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Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches
Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.
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A phenotype-driven and evidence-governed framework for knowledge graph enrichment and hypotheses discovery in population data
A phenotype-driven framework integrates GNNs, causal inference, probabilistic reasoning, and LLMs to expand knowledge graphs via multi-objective optimization that balances novelty, relevance, and evidence validation.