add: pandalm paper

_bibliography/pubs.bib

@@ -9,6 +9,9 @@ @inproceedings{qin2023generalizable
   booktitle={The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
   year={2023},
   corr={true},
+
+  arxiv={http://arxiv.org/abs/2306.04641},
+  code={https://github.com/microsoft/robustlearn}
 }
 
 @inproceedings{zhang2023domain,

_news/pandalm.md

@@ -4,4 +4,4 @@ date: 2023-05-04
 inline: true
 ---
 
-The large model for large model evaluation "PandaLM" is released on Github! [[PandaLM](https://github.com/WeOpenML/PandaLM)]
+The large model for large model evaluation "PandaLM" is released on Github! [[PandaLM](https://github.com/WeOpenML/PandaLM)] [[paper](https://arxiv.org/abs/2306.05087)]

_pages/publications.md

@@ -12,6 +12,7 @@ nav: true
 #### Preprints
 
 - PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie. [[arxiv](https://arxiv.org/abs/2306.04528)] [[code](https://github.com/microsoft/promptbench)]
+- PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization. Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang. [[arxiv](https://arxiv.org/abs/2306.05087)] [[code](https://github.com/WeOpenML/PandaLM)]
 - Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. Damien Teney, Jindong Wang, Ehsan Abbasnejad. [[arxiv](https://arxiv.org/abs/2305.16817)]
 - Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj. [[arxiv](https://arxiv.org/abs/2305.12715)]
 - Exploring Vision-Language Models for Imbalanced Learning. Yidong Wang, Zhuohao Yu, **Jindong Wang**, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang. [[arxiv](https://arxiv.org/abs/2304.01457)] [[code](https://github.com/Imbalance-VLM/Imbalance-VLM)]

_pages/research.md

@@ -17,8 +17,9 @@ Our research consists of the following topics with selected publications: [[View
 ##### New: large models
 
 - [arXiv'23] [PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts](https://arxiv.org/abs/2306.04528). Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie. [[code](https://github.com/microsoft/promptbench)]
+- [arXiv'23] [PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization](https://arxiv.org/abs/2306.05087). Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang. [[code](https://github.com/WeOpenML/PandaLM)]
 - **[ICLR'23 large model workshop]** [On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective](https://arxiv.org/abs/2302.12095). Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxin Jiao, Yue Zhang, and Xing Xie.
-- - **[arXiv'23]** [Exploring Vision-Language Models for Imbalanced Learning](https://arxiv.org/abs/2304.01457). Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang. [[code](https://github.com/Imbalance-VLM/Imbalance-VLM)]
+- [arXiv'23] [Exploring Vision-Language Models for Imbalanced Learning](https://arxiv.org/abs/2304.01457). Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang. [[code](https://github.com/Imbalance-VLM/Imbalance-VLM)]
 
 ##### Out-of-distribution (Domain) generalization and adaptation for distribution shift