add:week

2021Fall_AntNLP/README.md

@@ -45,18 +45,17 @@ Week   | Date | Speaker   | Paper   | Materials
 4 |9.29 | 杨晰 |[ACL21]Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks <br />[ACL21]ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning |
 5 |10.8 | 高怡 |[Survey] Some Papers about Few Shot Learning|
 6 |10.15| 纪焘  |[arxiv20] Seed the Views: Hierarchical Semantic Alignment for Contrastive Representation Learning<br /> [ACL21] COSY: COunterfactual SYntax for Cross-Lingual Understanding|
-7 |10.22 |刘宇芳 |[Survey] Shapley Value for Model Interpretability | 
+7 |10.22 |刘宇芳 |[Survey] Shapley Value for Model Interpretability | [Slides](https://github.com/AntNLP/seminar/tree/master/2021Fall_AntNLP/week7/1022.pdf)
 8 |10.29 | 李鹏|[Survey] Certified Defenses: A Survey | 
 9 |11.5 | 雷钲仪 | |
 10|11.12|黄子寅 | |
 11|11.19|杜威 | |
 12|11.26|周杰 | |
 13|12.3 |王志承|[EMNLP21]Transformer Feed-Forward Layers Are Key-Value Memories <br />[EMNLP21]Knowledge Neurons in Pretrained Transformers|[slides](https://drive.google.com/file/d/1pGjWLM9xJbJAh7Qslatfz4EwGea1JMkw/view?usp=sharing)|
-14|12.10| | |
-15|12.17| | |
+14|12.10|高怡 |Mixup in Meta-Learning |[slides](https://github.com/AntNLP/seminar/tree/master/2021Fall_AntNLP/week14/1210.pptx)
+15|12.17|杨晰 | |
 16|12.24|纪焘 | [Survey] Continual Lifelong Learning in NLP A Simple Survey | [slides](https://drive.google.com/file/d/1aM0bVLxKvrKKlMaI-X22ISsiMNzWndmr/view?usp=sharing)|
-17|12.31| | |
-18|1.7| | |
+17|12.31|刘宇芳 |Papers about Lottery Ticket Hypothesis | [slides](https://github.com/AntNLP/seminar/tree/master/2021Fall_AntNLP/week17/1231.pdf)
 
 
 

2022Spring_AntNLP/README.md

@@ -41,14 +41,14 @@ Welcome to AntNLP Seminar 2022 Spring. : )
 | Week | Date | Speaker | Paper | Materials |
 | ---- | ---- | ------- | ----- | --------- |
 | 1    | 3.11 | 纪焘    | PRETRAINED LANGUAGE MODEL IN CONTINUAL LEARNING: A COMPARATIVE STUDY <br>[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  <br> [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)          |
+| 2    | 3.18 | 刘宇芳  | Papers about Dataset Distillation | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week2)          |
+| 3    | 3.25 | 高怡    | Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation <br> On Episodes, Prototypical Networks, and Few-Shot Learning <br> TASK2VEC: Task Embedding for Meta-Learning      | [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 <br>  [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 <br>[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<br> [AAAI2022]Hard to Forget: Poisoning Attacks on Certified Machine Unlearning <br> [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 <br> [EMNLP21]MultiEURLEX – A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer <br>[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)          |
+| 9    | 5.6  | 高怡    |PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models<br> Noisy Channel Language Model Prompting for Few-Shot Text Classification <br> PILED: An Identify-and-Localize Framework for Few-Shot Event Detection      | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week9)          |
 | 10   | 5.13 | 杨晰    | [ACL18]Neural Open Information Extraction <br> [EMNLP20]Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction <br>[EMNLP20]OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction <br>[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 <br> [EMNLP20] Multi2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT | [Slides](https://github.com/AntNLP/seminar/tree/master/2022Spring_AntNLP/week12)          |