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arXiv AI By Ning Liu, Chuanneng Sun, Kristina Klinkner, Shervin Malmasi

Beyond Pairs: Your Language Model is Secretly Optimizing a Preference Graph

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The paper introduces Graph Direct Preference Optimization (GraphDPO), a generalization of Direct Preference Optimization that uses directed acyclic graphs to capture richer preference structures from multiple rollouts per prompt. GraphDPO encodes dominance relations as edges and optimizes a Plackett–Luce-inspired objective that aggregates supervision over dominated neighborhoods, preserving transitivity and handling ties or incomparable responses via an equivalence-class construction. Experiments on reasoning and program synthesis tasks show that this graph-structured approach outperforms traditional pairwise and listwise alignment objectives while maintaining linear per‑prompt complexity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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