add: two preprints

jindongwang · Oct 2, 2023 · 3aa1bc9 · 3aa1bc9
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diff --git a/_pages/publications.md b/_pages/publications.md
@@ -11,6 +11,8 @@ nav: true
 
 #### Preprints
 
+- DyVal: Graph-informed Dynamic Evaluation of Large Language Models. Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie. [[arxiv](https://arxiv.org/abs/2309.17167)]
+- Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj. [[arxiv](https://arxiv.org/abs/2309.17002)]
 - DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization. Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xiangyang Ji, Qiang Yang, Xing Xie. [[arxiv](https://arxiv.org/abs/2308.02282)]
 - Frustratingly Easy Model Generalization by Dummy Risk Minimization. Juncheng Wang, Jindong Wang, Xixu Hu, Shujun Wang, Xing Xie. [[arxiv](https://arxiv.org/abs/2308.02287)]
 - EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus. Cheng Li, Jindong Wang, Kaijie Zhu, Yixuan Zhang, Wenxin Hou, Jianxun Lian, Xing Xie. [[arxiv](https://arxiv.org/abs/2307.11760)]

diff --git a/_pages/research.md b/_pages/research.md
@@ -17,6 +17,7 @@ Our research consists of the following topics with selected publications: [[View
 ##### New: large models
 
 Evaluation: (website: https://llm-eval.github.io/)
+- [arXiv'23] [DyVal: Graph-informed Dynamic Evaluation of Large Language Models](https://arxiv.org/abs/2309.17167). Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie.
 - [arXiv'23] [A Survey on Evaluation of Large Language Models](https://arxiv.org/abs/2307.03109). Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie. [[code](https://github.com/MLGroupJLU/LLM-eval-survey)]
 - [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)]
@@ -25,6 +26,7 @@ Evaluation: (website: https://llm-eval.github.io/)
 
 
 Enhancement: (website: https://llm-enhance.github.io/)
+- [arXiv'23] [Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks](https://arxiv.org/abs/2309.17002). Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj.
 - [arXiv'23] [EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus](https://arxiv.org/abs/2307.11760). Cheng Li, Jindong Wang, Kaijie Zhu, Yixuan Zhang, Wenxin Hou, Jianxun Lian, Xing Xie.
 - [**IJCV'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)]
 - **[IEEE Data Engineering Bulletin'23]** FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning. Wang Lu, Xixu Hu, Jindong Wang, Xing Xie. [[arxiv](https://arxiv.org/abs/2302.13485)]