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This paper introduces CoDiffGRN, a co-evolutionary discrete diffusion framework for gene regulatory network inference, along with a new benchmark BEELINE-KGC for inductive evaluation. It achieves state-of-the-art performance in novel regulatory discovery.
This paper proposes AdaTKG, a method for temporal knowledge graph reasoning that uses adaptive memory to refine entity representations dynamically as new interactions occur, improving performance over static baselines.