Spain

automated scoring

theory of mind

psycholinguistics

stages 

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

**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

In this paper we present the first work on the automated scoring of mindreading ability in middle childhood and early adolescence. We create MIND-CA, a new corpus of 11,311 question-answer pairs in English from 1,066 children aged 7 to 14. We perform machine learning experiments and carry out extensive quantitative and qualitative evaluation. We obtain promising results, demonstrating the applicability of state-of-the-art NLP solutions to a new domain and task.

“What is on your mind?”: Automated Scoring of Mindreading in Childhood and Early Adolescence

technical paper

DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool

Best Paper Awards and Closing

LENOVO - multilingual, multimodal multi-turn smart conversational agent - MOLI

Expert.Ai - How to become an AI Expert Using the expert.ai NL API

Grammarly - Engineering at Grammarly

Interactive Key-Value Memory-augmented Attention for Image Paragraph Captioning

Modeling Long-distance Node Relations for KBQA with Global Dynamic Graph

A multivariate multiple regression approach to the mental lexicon - Harald Baayen

Catalan Cooking Social Event

The Computational Linguistics of Conversation Modeling Q&A - Amanda Stent

invited talk

https://d3smihljt9218e.cloudfront.net/transcript/4326/subtitle/58ca669318964bd3c0e0b2c4615b2359.vtt

English (automatic)

“What is on your mind?”: Automated Scoring of Mindreading in Childhood and Early Adolescence

Downloads

Next from COLING 2020

DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool

Similar lecture

Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children’s mindreading ability