Papers by Lingxiao Tang

2 papers
ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning (2026.acl-long)

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Challenge: Existing methods for code execution reasoning are limited by the difficulty of the training data.
Approach: They propose a model that uses reinforcement learning to reward correct answers from execution traces.
Outcome: The proposed model improves pass@1 by up to 5.9% on code generation tasks over strong baselines.
VividMed: Vision Language Model with Versatile Visual Grounding for Medicine (2025.naacl-long)

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Challenge: Vision Language Models (VLMs) have demonstrated promise in generating visually grounded responses, but their application in the medical domain is hindered by unique challenges.
Approach: They propose a vision language model with versatile visual grounding for medicine that generates semantic segmentation masks and instance-level bounding boxes.
Outcome: The proposed model can generate semantic segmentation masks and instance-level bounding boxes, and accommodates various imaging modalities, including both 2D and 3D data.

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