Papers by Jingxian Tang
Automated CAD Modeling Sequence Generation from Text Descriptions via Transformer-Based Large Language Models (2025.acl-long)
Copied to clipboard
JianXing Liao, Junyan Xu, Yatao Sun, Maowen Tang, Sicheng He, Jingxian Liao, Shui Yu, Yun Li, Xiaohong Guan
| Challenge: | Experimental results demonstrate that the proposed approach outperforms traditional methods in both accuracy and efficiency. |
| Approach: | They propose a language-guided framework that integrates large language models with computer-automated design to address these challenges. |
| Outcome: | The proposed framework outperforms traditional methods in accuracy and efficiency, providing a powerful tool for automating industrial workflows and generating complex CAD models from textual prompts. |
SHAPE: Stage-aware Hierarchical Advantage via Potential Estimation for LLM Reasoning (2026.acl-long)
Copied to clipboard
| Challenge: | Existing methods for process supervision fail to distinguish meaningful progress from mere verbosity . existing methods lack a coherent approach to process supervision . |
| Approach: | They propose a framework that formalizes reasoning as a trajectory through a state space of empirical solvability. |
| Outcome: | The proposed framework achieves an average accuracy gain of 3% with 30% reduced token consumption. |