Link to collaborative document of weekly report:
- paper reading讲解的时候要深入浅出,确保自己看懂了,再用通俗的话讲出来。关键是把文章工作讲清楚,motivation,方法部分,实验是否支撑,该工作的优点和缺点,对你个人工作的启发。每部分大概2~3页slides即可。最重要的是后面两部分,需要你自己对工作批判性的阅读。
- 时间暂定是周五晚上。 如果人不齐的话提前告知,视情况再确定时间。
- 分享的同学务必提前告知大家分享的论文,并在分享前update paper信息及slides到 HLT-HITSZ.github.io;新人权限开通请联系Jiachen DU。
- 参与者希望都能够提前把分享的paper进行相关背景的了解,积极提出问题及参与讨论。
Speakers | Papers | Slides | Others |
---|---|---|---|
LanGongqiang | EMNLP 2019 Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks | [slide] | - |
LiuYuhan | EMNLP 2019 A logic-Driven Framework for Consistency of Neural Models | [slide] | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
SuHang | ACL 2019 Do you know that Florence is packed with visitors?Evaluating state-of-the-art models of speaker commitment | [slide] | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
JiamingLi | ACL 2019 Bridging the Gap between Training and Inference | [slide] | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
JianzhuBao | ACL 2017 Neural End-to-End Learning for Computational Argumentation Mining | [slide] | - |
- | arXiv 2016 Here’s My Point: Joint Pointer Architecture for Argument Mining | - | - |
- | ACL 2019 Classification and Clustering of Arguments with Contextualized Word Embeddings | - | - |
- | ACL 2019 Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction | - | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
BinLiang | NAACL 2019 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | [slide] | - |
- | arXiv 2019 How multilingual is Multilingual BERT? | - | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
YipingYin | ACL 2019 Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks | [slide] | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
BinLiang | COLING 2016 Effective LSTMs for Target-Dependent Sentiment Classification | [slide] | - |
- | EMNLP 2016 Attention-based LSTM for Aspect-level Sentiment Classification | - | - |
- | EMNLP 2016 Aspect Level Sentiment Classification with Deep Memory Network | - | - |
- | EMNLP 2016 A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis | - | - |
- | ACL 2018 Aspect Based Sentiment Analysis with Gated Convolutional Networks | - | - |
- | AAAI 2018 Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM | - | - |
JianzhuBao | COLING 2016 Multimodal Attention for Neural Machine Translation | [slide] | - |
- | ACL 2017 Attention Strategies for Multi-Source Sequence-to-Sequence Learning | - | - |
- | NAACL 2019 Probing the Need for Visual Context in Multimodal Machine Translation | - | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
XiuCheng | ICLR 2017 SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS | - | - |
- | NIPC 2017 Inductive Representation Learning on Large Graphs | - | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
ZhiyuanWen | Arxiv Focal Loss for Dense Object Detection | [slide] | - |
- | Technical Report Multi-class classification with focal loss for imbalanced datasets | - | - |
Speakers | Papers | Slides | Others |
---|---|---|---|
jiachendu | ICLR 2019 LEARNING TO REPRESENT EDITS | [slide] | - |
- | Text Infilling | - | - |
- | TIGS: An Inference Algorithm for Text Infilling with Gradient Search | - | - |