Thailand

event extraction

transfer learning

information extraction

**Welcome to ACL-IJCNLP 2021!**

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP). 

This Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) was to be held in Bangkok, Thailand, during August 1-6, 2021 and is now virtual on the Underline platform.

As in previous years, the program of the conference includes a poster session, tutorials, workshops and demonstrations in addition to the main conference.


We were able to keep the registration fees similar to those charged for the virtual ACL 2020. The one fee allows attendance at the main conference and any/all tutorials and workshops. These fees would be $125 Regular Early and $175 Regular Late; $50 Student Early and $75 Student Late. Early registration closes at midnight July 11, 2021 (Eastern Daylight Time).

**Reminder:** It is ACL’s policy that at least one author of each accepted paper (including ACL Finding papers) must register for the conference.

**Reminder2:** Underline site will open closer to the event. If you already registered you will receive access detail

Registration is now open

ACL 2021

Event extraction has long been a challenging task, addressed mostly with supervised methods that require expensive annotation and are not extensible to new event ontologies. In this work, we explore the possibility of zero-shot event extraction by formulating it as a set of Textual Entailment (TE) and/or Question Answering (QA) queries (e.g. "A city was attacked" entails "There is an attack"), exploiting pretrained TE/QA models for direct transfer. On ACE-2005 and ERE, our system achieves acceptable results, yet there is still a large gap from supervised approaches, showing that current QA and TE technologies fail in transferring to a different domain. To investigate the reasons behind the gap, we analyze the remaining key challenges, their respective impact, and possible improvement directions.

Zero-shot Event Extraction via Transfer Learning: Challenges and Insights

technical paper

PRAL: A Tailored Pre-Training Model for Task-Oriented Dialog Generation

A Systematic Investigation of KB-Text Embedding Alignment at Scale

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model

Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction

Fusing Context Into Knowledge Graph for Commonsense Question Answering

Survival text regression for time-to-event prediction in conversations

Minimax and Neyman–Pearson Meta-Learning for Outlier Languages

Grammar-Constrained Neural Semantic Parsing with LR Parsers

https://assets.underline.io/transcript/19224/subtitle/4296acc04190955cb83b33bb29236ad5.vtt

https://assets.underline.io/transcript/20645/subtitle/61a0fe31be68103dad18ea44c302f4ee.vtt

English (automatic)

English

Zero-shot Event Extraction via Transfer Learning: Challenges and Insights

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Next from ACL 2021

PRAL: A Tailored Pre-Training Model for Task-Oriented Dialog Generation

Similar lecture

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