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2022Spring_AntNLP

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AntNLP Seminar -- 2022 Spring

Time: 3:00 pm, Friday

Venue: B914, Science Building; Online

Welcome to AntNLP Seminar 2022 Spring. : )

On Papers

  • Please choose recent papers (2021, 2020) 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, the followings (and a list here) are of great importance
    • syntactic/semantic parsing
    • entity/relation/event extraction
    • distributed/distributional/compositional semantics
    • MT/QA/Dialog
    • (deep) learning algorithms
  • 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 3.11 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
2 3.18 刘宇芳 Papers about Dataset Distillation Slides
3 3.25 高怡 Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation
On Episodes, Prototypical Networks, and Few-Shot Learning
TASK2VEC: Task Embedding for Meta-Learning
Slides
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
5 4.8 杜威 [EMNLP21]Zero-Shot Information Extraction as a Unified Text-to-Triple Translation Slides
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
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
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
9 5.6 高怡 PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models
Noisy Channel Language Model Prompting for Few-Shot Text Classification
PILED: An Identify-and-Localize Framework for Few-Shot Event Detection
Slides
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
11 5.20 李鹏 Slides
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
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
15 6.17 休息
16 6.24 汪杰
李雨倩
Slides

F.A.Q.

  1. How to fill the slots and upload your slides?