Shared Task

The First Shared Task on Fine-Tuning LLMs for Ukrainian

 

The Third UNLP organizes the first Shared Task on Fine-Tuning Large Language Models (LLMs) for Ukrainian.

 

Important Dates

 

January 15, 2024 — Shared task announcement

February 12, 2024 — Second call for participation; release of train data

February 16, 2024 — Release of test data to registered participants

February 24, 2024 — Registration deadline; release of open questions

February 26, 2024 — Submission of system responses

March 4, 2024 — Results of the Shared Task announced

March 6, 2024 — Shared Task paper due

March 27, 2024 — Notification of acceptance

April 5, 2024 — Camera-ready papers due

May 25, 2024 — Workshop

 

Task Description

 

This Shared Task aims to challenge and assess LLMs’ capabilities to understand and generate Ukrainian, paving the way for LLM development in Slavic languages.

 

In this shared task, your goal is to instruction-tune a large language model that can answer questions and perform tasks in Ukrainian. The model should possess knowledge of Ukrainian history, language, and literature, as well as common knowledge, and should be capable of generating fluent and factually accurate responses.

 

You can find the detailed instructions, limitations, baseline, and evaluation sample at https://github.com/unlp-workshop/unlp-2024-shared-task.

 

Registration

 

Teams that intend to participate should register by filling in this form.

 

Publication

 

Participants in the shared task are invited to submit a paper to the UNLP 2024 workshop. Submitting a paper is not mandatory for participating in the Shared Task. Papers must follow the workshop submission instructions and will undergo regular peer review. Their acceptance will not depend on the results obtained in the shared task, but on the quality of the paper. Accepted papers will appear in the ACL anthology and will be presented at a session of UNLP 2024 specially dedicated to the Shared Task.

 

Link for paper submission: https://softconf.com/lrec-coling2024/unlp2024/