Papers by Heng Lian
LiveCANNBench: Benchmark SWE AI Coding for Ascend CANN (2026.findings-acl)
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Sijie Wang, Kai Zhao, Wee Peng Tay, Shuo Zhang, Chengwen Liu, Quanjiang Guo, Ren Junhao, Xin Li, Heng Lian, Jingdi Lei, Rui She, Huacan Wang, Ronghao Chen
| Challenge: | Recent advances in agents have enabled multi-file, multi-language, and dependency-aware AI coding. |
| Approach: | They propose an SWE-level benchmark for AI coding in the Huawei Ascend CANN software stack. |
| Outcome: | The proposed benchmark is constructed from real-world CANN repositories and consists of over 400 task instances spanning multiple file, multi-language, and execution-aware coding challenges. |
R-Tuning: Instructing Large Language Models to Say ‘I Don’t Know’ (2024.naacl-long)
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Hanning Zhang, Shizhe Diao, Yong Lin, Yi Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
| Challenge: | Existing methods for instruction tuning force the model to complete a sentence no matter whether it knows the knowledge or not. |
| Approach: | They propose a new approach to tuning large language models to refrain from answering questions beyond its parametric knowledge by identifying the disparity in parametric and parametric information. |
| Outcome: | The proposed approach improves a model’s ability to answer known questions and refrain from answering unknown questions. |