💡Text + graphs have powered NLP tasks for a long time. But key questions remain: How do their representations relate to each other during learning? How does that relationship impact task performance? Under what conditions is integrating text and graph more beneficial? In our paper, "R²-CoD: Understanding Text-Graph Complementarity in Relational Reasoning via Knowledge Co-Distillation", we take an analysis-driven perspective and uncover a spectrum of behaviors from complementarity → partial alignment → full alignment. 📜arxiv.org/abs/2508.01475 🧵[1/8]

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