Papers by Jianliang Liu

    1 papers
    Draft, Verify, Restore: Self-Refining Historical Inscription Restoration with a Unified MLLM (2026.acl-long)

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    Challenge: Existing methods for end-to-end historical inscription restoration rely on task-separated pipelines with irreversible error accumulation and patch-based generation that sacrifices page-level consistency.
    Approach: They propose a unified MLLM for end-to-end historical inscription restoration that integrates draft-guided localization and Hierarchical self-refinement to enable accurate damage localization.
    Outcome: The proposed model achieves superior performance in both text restoration accuracy and appearance restoration quality.

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