Competition

KUIS-AI Shared Task Repository, see competition repo and website.

Kind Rules for our Repo

Please try to obey the "rules" of our repo, to make everything as convenient as possible. These are to make everything more easier for everyone. :)

1. Set your environment from scratch. If you installed new packages, please document each of the packges with their versions.
2. When you are implementing a new model, for a specific task, create a subfolder as taskX_name_vY, where X and Y is the task and model versions respectively. For example: ./task1/task1_emrecan_v1 and ./task1/task1_tilek_v1. Initial subfolders are already created for you.
3. Update your To Do's in your subfolder, frequently. By this, others can follow your progress easily. I will add your To Do's inside the top-level README, one by one.
4. Try to add helper comments to your code. This way, others can read your code easily.
5. Add your research materials or your suggested materials to Suggested Research Materials section in this README file.
   

At the end, lets beat this competition!

Calendar of the Competition

Days left: 7

Week	Mon	Tue	Wed	Thu	Fri	Sat	Sun
33	15📍	16	17	18	19	20	21
34	22🎯	23	24	25*	26	27	28
35	29	30	31	1	2	3	4

Important Deadlines:

July 8, 2022: Get a baseline score for each task with each language (6 Languages x 3 tasks = 18 results).
===> August 7, 2022: Release of testing data (including surprise languages)
===> August 14, 2022: Deadline to release external data and resources used in systems
===> August 15, 2022: Deadline for our scores
===> August 22, 2022: Deadline for submission of systems
===> August 25, 2022: Release of rankings and results
===> September 15, 2022: Deadline for submitting system description papers
===> October 10, 2022: Paper notifications
===> November 9, 2022: Camera-ready papers and posters due
===> December 8, 2022: Workshop

Environment Set-up

Please do the followings to run the baselines successfully, i.e. "taskx_emrecan_v1":

conda create --name taskx_emrecan_v1 python=3.7
source activate taskx_emrecan_v1

pip install torch==1.12.0
pip install numpy==1.21.6
pip install matplotlib==3.5.2

You can check your installed packages in your environment by doing conda list. Here is mine. Please open an issue for any version conflicts.

Suggested Research Materials:

Please add/update this section whenever you find something useful.

1. Morphology Without Borders: Clause-Level Morphological Annotation
2. Morphological Inflection Generation with Hard Monotonic Attention
3. On Biasing Transformer Attention Towards Monotonicity
4. Monotonic Multihead Attention
5. Applying the Transformer to Character-level Transduction
6. Pushing the Limits of Low-Resource Morphological Inflection
7. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
8. Prefix-Tuning: Optimizing Continuous Prompts for Generation
9. OpenPrompt repo
10. Exact Hard Monotonic Attention for Character-Level Transduction
11. Breaking Character: Are Subwords Good Enough for MRLs After All?
12. Neural Morphological Tagging models
13. Exploring Pretrained Models for Joint Morpho-Syntactic Parsing of Russian
14. MorphoRuEval-2017: an Evaluation Track for the Automatic Morphological Analysis Methods