diff --git a/2022Spring_AntNLP/readme.md b/2022Spring_AntNLP/readme.md index d2274db..86a7074 100644 --- a/2022Spring_AntNLP/readme.md +++ b/2022Spring_AntNLP/readme.md @@ -1,8 +1,8 @@ -# AntNLP Seminar -- 2021 Spring +# AntNLP Seminar -- 2022 Spring -Time: **9:00 am, Friday** +Time: **3:00 pm, Friday** -Venue: B914, Science Building. +Venue: B914, Science Building; Online Welcome to AntNLP Seminar 2022 Spring. : ) @@ -40,23 +40,22 @@ Welcome to AntNLP Seminar 2022 Spring. : ) | Week | Date | Speaker | Paper | Materials | | ---- | ---- | ------- | ----- | --------- | -| 1 | 3.4 | 纪焘 | | | -| 2 | 3.11 | 刘宇芳 | | | -| 3 | 3.18 | 高怡 | | | -| 4 | 3.25 | 杨晰 | | | -| 5 | 4.1 | 杜威 | | | -| 6 | 4.8 | 王志承 | | | -| 7 | 4.15 | 李雨倩 | | | -| 8 | 4.22 | 汪杰 | | | -| 9 | 4.29 | | | | -| 10 | 5.6 | | | | -| 11 | 5.13 | | | | -| 12 | 5.20 | | | | -| 13 | 5.27 | | | | -| 14 | 6.3 | | | | -| 15 | 6.10 | | | | -| 16 | 6.17 | | | | -| 17 | 6.24 | | | | +| 1 | 3.11 | 纪焘 | PRETRAINED LANGUAGE MODEL IN CONTINUAL LEARNING: A COMPARATIVE STUDY
[TACL2021]Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week1) | +| 2 | 3.18 | 刘宇芳 | Dataset Distillat
[ICLR2021]DATASET CONDENSATION WITH GRADIENT MATCHING | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week2) | +| 3 | 3.25 | 高怡 | | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week3) | +| 4 | 4.1 | 杨晰 | [EMNLP19] Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks
[EMNLP20] Inducing Target-Specific Latent Structures for Aspect Sentiment Classification | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week4) | +| 5 | 4.8 | 杜威 |[EMNLP21]Zero-Shot Information Extraction as a Unified Text-to-Triple Translation | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week5) | +| 6 | 4.15 | 王志承 |[ICLR2018]Measuring the Intrinsic Dimension of Objective Landscapes
[ACL2021]Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week6) | +| 7 | 4.22 | 刘宇芳 | [ICML2020]Certified Data Removal from Machine Learning Models
[AAAI2022]Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
[AISTATS2021]Approximate Data Deletion from Machine Learning Models | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week7) | +| 8 | 4.29 | 纪焘 | [ACL2022]Knowledge Neurons in Pretrained Transformers
[EMNLP21]MultiEURLEX – A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer
[ACL2022]Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week8) | +| 9 | 5.6 | 高怡 | | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week9) | +| 10 | 5.13 | 杨晰 | [ACL18]Neural Open Information Extraction
[EMNLP20]Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction
[EMNLP20]OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction
[EMNLP21]Maximal Clique Based Non-Autoregressive Open Information Extraction | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week10) | +| 11 | 5.20 | 李鹏 | | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week11) | +| 12 | 5.27 | 杜威 |[EMNLP16] Creating a Large Benchmark for Open Information Extraction
[EMNLP20] Multi2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week12) | +| 13 | 6.3 | 休息 | | | +| 14 | 6.10 | 王志承 |[ACL2022]An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
[ACL2022]Prototypical Verbalizer for Prompt-based Few-shot Tuning | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week14) | +| 15 | 6.17 | 休息 | | | +| 16 | 6.24 | 汪杰
李雨倩 | | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week16) | ------ @@ -69,4 +68,4 @@ Welcome to AntNLP Seminar 2022 Spring. : ) - Peng Li, [ruhao9805@gmail.com](mailto:ruhao9805@gmail.com) - Tao Ji, [taoji.cs@gmail.com](mailto:taoji.cs@gmail.com) - Yang Wei, [i@godweiyang.com](mailto:i@godweiyang.com) -- any quesitons, please feel free to contact us. \ No newline at end of file +- any quesitons, please feel free to contact us. diff --git a/2022Spring_AntNLP/week10/0513.pdf b/2022Spring_AntNLP/week10/0513.pdf new file mode 100644 index 0000000..095dd88 Binary files /dev/null and b/2022Spring_AntNLP/week10/0513.pdf differ diff --git a/2022Spring_AntNLP/week12/0605.pptx b/2022Spring_AntNLP/week12/0605.pptx new file mode 100644 index 0000000..826c330 Binary files /dev/null and b/2022Spring_AntNLP/week12/0605.pptx differ diff --git a/2022Spring_AntNLP/week14/0610.pptx b/2022Spring_AntNLP/week14/0610.pptx new file mode 100644 index 0000000..6740628 Binary files /dev/null and b/2022Spring_AntNLP/week14/0610.pptx differ diff --git a/2022Spring_AntNLP/week2/0318.pdf b/2022Spring_AntNLP/week2/0318.pdf new file mode 100644 index 0000000..c75ecde Binary files /dev/null and b/2022Spring_AntNLP/week2/0318.pdf differ diff --git a/2022Spring_AntNLP/week4/0401.pdf b/2022Spring_AntNLP/week4/0401.pdf new file mode 100644 index 0000000..ad06759 Binary files /dev/null and b/2022Spring_AntNLP/week4/0401.pdf differ diff --git a/2022Spring_AntNLP/week5/0408.pptx b/2022Spring_AntNLP/week5/0408.pptx new file mode 100644 index 0000000..8570c41 Binary files /dev/null and b/2022Spring_AntNLP/week5/0408.pptx differ diff --git a/2022Spring_AntNLP/week6/0415.pptx b/2022Spring_AntNLP/week6/0415.pptx new file mode 100644 index 0000000..9708240 Binary files /dev/null and b/2022Spring_AntNLP/week6/0415.pptx differ diff --git a/2022Spring_AntNLP/week7/0422.pdf b/2022Spring_AntNLP/week7/0422.pdf new file mode 100644 index 0000000..f4ce92f Binary files /dev/null and b/2022Spring_AntNLP/week7/0422.pdf differ diff --git a/2022Spring_AntNLP/week8/0429.pdf b/2022Spring_AntNLP/week8/0429.pdf new file mode 100644 index 0000000..e427f52 Binary files /dev/null and b/2022Spring_AntNLP/week8/0429.pdf differ diff --git a/2023Spring_StatNLP/readme.md b/2023Spring_StatNLP/readme.md new file mode 100644 index 0000000..1da1c0a --- /dev/null +++ b/2023Spring_StatNLP/readme.md @@ -0,0 +1,43 @@ +# Statistical Natural Language Processing Seminar -- 2023 Spring + +Time: **9:50, Thursday** + +Venue: Tin Ka Ping Building 234 (田家炳楼234) + +Welcome to StatNLP Seminar 2023 Spring. : ) + +## On Papers + +- Please choose recent papers (2023, 2022, 2021) from top NLP/AI venues. A (incomplete) list is + - NLP: ACL, TACL, EMNLP, NAACL, EACL + - ML: ICML, NeurIPS, AISTATS, JMLR, ICLR + - AI: AAAI, IJCAI + - IR/DM: SIGIR, CIKM, WSDM, KDD, WWW +- While we are interested in a broad range of NLP/AI topics, this year we will pay special attentions on two themes + - foundation models (pre-training models) + - explaining methods +- We hope that, with high probability, you choose papers from [here](https://github.com/AntNLP/seminar/blob/master/2023Spring_StatNLP/2023-paper-list.md) +- other materials with broad interests are welcome (e.g., tutorials form top conferences, high-quality surveys). + +## For Presenters + +- Please fill your slots in the Agenda at least one week before your presentation. + + - Please format Paper fields with *[venue+year]title* (e.g. [ACL21]A Good Paper). +- Please upload your slides, and add links to them in Slides fields. + +- Besides technical novelties, please give enough background knowledge in case people are unfamiliar with your topic. + +- It would be great to keep your presentation within 60 min. + +## For Audiences + +- Please read abstract/introduction sections before the seminar. + +## Agenda + + + +| Week | Date | Speaker | Paper | Materials | +| ---- | ---- | ------- | ----- | --------- | +| 1 | 3.2 | | | | \ No newline at end of file diff --git a/readme.md b/readme.md new file mode 100644 index 0000000..1da1c0a --- /dev/null +++ b/readme.md @@ -0,0 +1,43 @@ +# Statistical Natural Language Processing Seminar -- 2023 Spring + +Time: **9:50, Thursday** + +Venue: Tin Ka Ping Building 234 (田家炳楼234) + +Welcome to StatNLP Seminar 2023 Spring. : ) + +## On Papers + +- Please choose recent papers (2023, 2022, 2021) from top NLP/AI venues. A (incomplete) list is + - NLP: ACL, TACL, EMNLP, NAACL, EACL + - ML: ICML, NeurIPS, AISTATS, JMLR, ICLR + - AI: AAAI, IJCAI + - IR/DM: SIGIR, CIKM, WSDM, KDD, WWW +- While we are interested in a broad range of NLP/AI topics, this year we will pay special attentions on two themes + - foundation models (pre-training models) + - explaining methods +- We hope that, with high probability, you choose papers from [here](https://github.com/AntNLP/seminar/blob/master/2023Spring_StatNLP/2023-paper-list.md) +- other materials with broad interests are welcome (e.g., tutorials form top conferences, high-quality surveys). + +## For Presenters + +- Please fill your slots in the Agenda at least one week before your presentation. + + - Please format Paper fields with *[venue+year]title* (e.g. [ACL21]A Good Paper). +- Please upload your slides, and add links to them in Slides fields. + +- Besides technical novelties, please give enough background knowledge in case people are unfamiliar with your topic. + +- It would be great to keep your presentation within 60 min. + +## For Audiences + +- Please read abstract/introduction sections before the seminar. + +## Agenda + + + +| Week | Date | Speaker | Paper | Materials | +| ---- | ---- | ------- | ----- | --------- | +| 1 | 3.2 | | | | \ No newline at end of file