diff --git a/_bibliography/pubs.bib b/_bibliography/pubs.bib index d0eef9814621..12ad44f4f09c 100644 --- a/_bibliography/pubs.bib +++ b/_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}, diff --git a/_news/acl23.md b/_news/acl23.md new file mode 100644 index 000000000000..c2f5e875086b --- /dev/null +++ b/_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)] \ No newline at end of file diff --git a/_news/kdd23tutorial.md b/_news/kdd23tutorial.md new file mode 100644 index 000000000000..7169af87706d --- /dev/null +++ b/_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"! \ No newline at end of file diff --git a/_news/pandalm.md b/_news/pandalm.md new file mode 100644 index 000000000000..ed15650c28f2 --- /dev/null +++ b/_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)] diff --git a/_pages/publications.md b/_pages/publications.md index 9b24d42ce050..3ed48343fa79 100644 --- a/_pages/publications.md +++ b/_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)] diff --git a/_pages/research.md b/_pages/research.md index bda3c3c94aee..ef22971959f7 100644 --- a/_pages/research.md +++ b/_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