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SECOND CALL FOR PARTICIPATION
Advanced Language Processing School (ALPS)
January, 17-22 2021
Autrans (Grenoble area) - France
We are opening the registration for the first Advanced Language Processing School (ALPS) in Grenoble, co-organized by University Grenoble Alpes and Naver Labs Europe.
*Target Audience*
This is a winter school covering advanced topics in NLP, and we are primarily targeting doctoral students and advanced (research) masters. A few slots will also be reserved for academics and persons working in research-heavy positions in industry.
*Characteristics*
This winter school aims to provide talks of renowned NLP researchers, as well as creating an ideal environment to foster collaborations
The speakers are:
- Isabelle Augenstein: _Interpretability and Explainability for NLP_
- Tim Baldwin: _Natural Language Processing for User Generated Content_
- Kyunghyun Cho: _Neural Sequence Modeling: Learning and Inference_
- Yejin Choi: _Neural Commonsense Knowledge and Reasoning_
- Grzegorz Chrupała: _Visually Grounded Models of Spoken Language and their Analysis_
- Claire Gardent: _Neural approaches to Natural Language Generation_
- Sanjeev Khudanpur: _Recent Advances in Automatic Speech Recognition (TBC)_
In addition to the talks, an important aspect of this school is the interaction between participants. The registration fee covers full board in a residence close to a ski resort, and some of the afternoons there will be organised social activities.
In view of the current public health situation, we are preparing to hold the event virtually in case it will not be possible to do so physically in January. Registration fees will be adapted in that case.
*Application*
To apply to this winter school, please follow the instructions at http://alps.imag.fr/index.php/application/ <http://alps.imag.fr/index.php/application/> . The deadline for applying is July 31st, and we will notify acceptance in September
*Contact*
Website: http://alps.imag.fr/
Contact: alps2021(a)univ-grenoble-alpes.fr
Apologies for cross-posting
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We are inviting researchers to participate in a shared task at FIRE 2020 on
sentiment analysis for Dravidian languages in code-mixed text.
Website: https://dravidian-codemix.github.io/2020/
The goal of this task is to identify sentiment polarity of the code-mixed
dataset of comments/posts in Dravidian Languages (Malayalam-English and
Tamil-English) collected from social media. The comment/post may contain
more than one sentence but the average sentence length of the corpora is 1.
Each comment/post is annotated with sentiment polarity at the comment/post
level. This dataset also has class imbalance problems depicting real-world
scenarios. Our proposal aims to encourage research that will reveal how
sentiment is expressed in code-mixed scenarios on social media.
The participants will be provided development, training and test dataset.
Key Dates:
Release of Trail data: 10 June
Release of Training data: 10 June
Release of Test data: 1 August
Run submission deadline: 20 August
Results declared: 31 August
Paper submission: 20 September
Revised paper: 30 October.
10th-13th December - FIRE 2020