add: news

_bibliography/pubs.bib

@@ -3,6 +3,16 @@
 
 @string{aps = {American Physical Society,}}
 
+@inproceedings{yang2023glue,
+  title={GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective},
+  author={Yang, Linyi and Zhang, Shuibai and Qin, Libo and Li, Yafu and Wang, Yidong and Liu, Hanmeng and Wang, Jindong and Xie, Xing and Zhang, Yue},
+  booktitle={The 61st Annual Meeting of the Association for Computational Linguistics (ACL) Findings},
+  year={2023},
+
+  arxiv={https://arxiv.org/abs/2211.08073},
+  code={https://github.com/YangLinyi/GLUE-X}
+}
+
 @inproceedings{lu2023generalized,
   title={Out-of-distribution Representation Learning for Time Series Classification},
   author={Lu, Wang and Wang, Jindong and Sun, Xinwei and Chen, Yiqiang and Xie, Xing},

_news/acl23.md

@@ -0,0 +1,7 @@
+---
+layout: post
+date: 2023-05-03
+inline: true
+---
+
+Our paper "GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective" is accepted by ACL 2023 findings! [[paper](https://arxiv.org/abs/2211.08073)]

_news/kdd23tutorial.md

@@ -0,0 +1,7 @@
+---
+layout: post
+date: 2023-05-01
+inline: true
+---
+
+We will give a tutorial on KDD 2023 named "Trustworthy machine learning: generalization, robustness, and interpretability"! 

_news/pandalm.md

@@ -0,0 +1,7 @@
+---
+layout: post
+date: 2023-05-04
+inline: true
+---
+
+The large model for large model evaluation "PandaLM" is released on Github! [[PandaLM](https://github.com/WeOpenML/PandaLM)]

_pages/publications.md

@@ -13,7 +13,6 @@ nav: true
 
 - 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)]
 - An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning. Hao Chen, Yue Fan, Yidong Wang, **Jindong Wang**, Bernt Schiele, Xing Xie, Marios Savvides, Bhiksha Raj. [[arxiv](https://arxiv.org/abs/2211.11086)] 
-- GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective. Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, **Jindong Wang**, Xing Xie, Yue Zhang. [[arxiv](https://arxiv.org/abs/2211.08073)]
 - FIXED: Frustratingly Easy Domain Generalization with Mixup. Wang Lu, **Jindong Wang**, Han Yu, Lei Huang, Xiang Zhang, Yiqiang Chen, Xing Xie. [[arxiv](https://arxiv.org/abs/2211.05228)]
 - Domain-Specific Risk Minimization for Out-of-Distribution Generalization. YiFan Zhang, **Jindong Wang**, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Xing Xie, and Dacheng Tao. [[arxiv](https://arxiv.org/pdf/2208.08661.pdf)]
 - Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets. Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, and Marios Savvides. [[arxiv](https://arxiv.org/abs/2208.07463)]

_pages/research.md

@@ -15,7 +15,8 @@ Our research consists of the following topics with selected publications: [[View
 
 ##### Out-of-distribution (Domain) generalization and adaptation for distribution shift
 
-- **[ICLR'23]** [Out-of-distribution Representation Learning for Time Series Classification](https://arxiv.org/abs/2209.07027). Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, and Xing Xie. 
+- **[ICLR'23]** [Out-of-distribution Representation Learning for Time Series Classification](https://arxiv.org/abs/2209.07027). Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, and Xing Xie.
+- **[ACL'23 findings]** [GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective](https://arxiv.org/abs/2211.08073). Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, **Jindong Wang**, Xing Xie, Yue Zhang.
 - **[TKDE'22]** [Generalizing to Unseen Domains: A Survey on Domain Generalization](https://arxiv.org/abs/2103.03097). Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, and Philip S. Yu.
 - **[TMLR'22]** [Domain-invariant Feature Exploration for Domain Generalization](https://arxiv.org/abs/2207.12020). Wang Lu, Jindong Wang, Haoliang Li, Yiqiang Chen, and Xing Xie.
 - **[UbiComp'22]** [Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition](http://arxiv.org/abs/2206.06629). Wang Lu, Jindong Wang, Yiqiang Chen, Sinno Pan, Chunyu Hu, and Xin Qin.
@@ -27,6 +28,7 @@ Our research consists of the following topics with selected publications: [[View
 - Open-source: 
   - [Transfer learning](https://github.com/jindongwang/transferlearning) [![Transfer learning repo](https://img.shields.io/github/stars/jindongwang/transferlearning?style=social)](https://github.com/jindongwang/transferlearning)
   - robustlearn: A unified repo for robust machine learning, such as OOD and adversarial robustness: [robustlearn](https://github.com/microsoft/robustlearn) [![robustlearn](https://img.shields.io/github/stars/microsoft/robustlearn?style=social)](https://img.shields.io/github/stars/microsoft/robustlearn)
+  - PandaLM: [PandaLM](https://github.com/WeOpenML/PandaLM) [![robustlearn](https://img.shields.io/github/stars/WeOpenML/PandaLM?style=social)](https://img.shields.io/github/stars/WeOpenML/PandaLM)
 
 ##### Semi-supervised learning for low-resource learning