Papers by Yuhao Shang

2 papers
CodeFort: Robust Training for Code Generation Models (2024.findings-emnlp)

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Challenge: Existing research efforts to improve code generation models are inadequate . code generation model performance is degraded under small perturbations .
Approach: They propose a framework to improve the robustness of code generation models by generalizing code perturbations to enrich training data and enabling various robust training strategies.
Outcome: The proposed framework increases pass rates and robustness drop rate against code-syntax perturbations.
Enhancing Agentic Textual Graph Retrieval with Synthetic Stepwise Supervision (2026.acl-long)

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Challenge: Existing methods for integrating textual graphs with LLMs are limited by symbolic inference and high annotation costs.
Approach: They propose a textual graph reasoning framework that integrates textual diagrams with large language models.
Outcome: The proposed approach achieves 15.6% accuracy and 17.2% in F1 score on three common datasets.

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