all-entity ranking 1continuous-time dynamic graphs 1evaluation methodology 1negative sampling 1next-destination prediction 1
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cs.AI2026
LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting
Minwoo Yu, Young-guk Ha
Continuous-time dynamic graph models predict future links by compressing past interactions into neural states. Although effective for forecasting, this computation obscures which e…
cs.AI2026
Back to All-Entity Ranking: Sampler-Dependent Evaluation in Continuous-Time Dynamic Graphs
Minwoo Yu, Young-guk Ha
The paper shows that using sampled negative destinations in continuous-time dynamic graph next-destination prediction can change model rankings, and proposes evaluating with all-en…
cs.AI2026
Relevance Is Not Permission: Warranted Attention for Value Contributions
Minwoo Yu, Young-guk Ha
Relevance is not permission. Attention lets a model read key-value items related to the current query, but it does not guarantee that the value contribution of such an item becomes…