mlsanityData to 7 Oct 2026

The PLLuM Instruction Corpus

arXiv 2511.17161 ↗First posted 21 Nov 2025cs.CL cs.AIcited by 1

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Abstract (arXiv)

This paper describes the instruction dataset used to fine-tune a set of transformer-based large language models (LLMs) developed in the PLLuM (Polish Large Language Model) project. We present a functional typology of the organic, converted, and synthetic instructions used in PLLuM and share some observations about the implications of using human-authored versus synthetic instruction datasets in the linguistic adaptation of base LLMs. Additionally, we release the first representative subset of the PLLuM instruction corpus (PLLuMIC), which we believe to be useful in guiding and planning the development of similar datasets for other LLMs.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 43 of its 93 references that are in the map. First posted on arXiv 21 Nov 2025.

Builds on

43 of 93 references.

References · 43

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31 more
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  1. 2026What properties of reasoning supervision are associated with improved downstream model quality?cited by 0