Papers by Lingfang Zeng

2 papers
Adversarial Alignment with Anchor Dragging Drift (A3D2): Multimodal Domain Adaptation with Partially Shifted Modalities (2025.acl-long)

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Challenge: Domain adaptation is underexplored in multimodal learning environments due to expensive data collection and annotation.
Approach: They propose a bi-alignment scheme to perform drift-drift and anchor-driving matching with partially shifting anchors.
Outcome: The proposed approach achieves superior performance compared with state-of-the-art approaches.
SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning (2026.findings-acl)

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Challenge: Existing approaches to training GUI agents on dynamic tasks are based on SFT or Behavior Cloning.
Approach: They propose a framework that integrates global trajectory insights directly into offline learning . they reconstruct diverse rollout candidates from static data and detect first failure point .
Outcome: The proposed framework improves long-horizon task completion rates and robustness compared to baselines.

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