Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements
Updated 50 min ago · first seen 11 Sept 2026
paper_01M294G6BT70TRZYJYTWT5EQXH
- Published
- 11 Sept 2026
- T1 · 50 min ago
- arXiv
- 2609.09425
- T1 · 50 min ago
- Category
- cs.CL
- T1 · 50 min ago
Abstract
Educational data filters have become a practical way to improve language-model pre-training, but most filters treat educational value as a single scalar property. This may be too broad for some applications, especially if the data set already features a high density of educational material. Useful learning material needs to be accurate, engaging, well structured, and appropriate for the intended audience and application (e.g. learner- vs teacher-facing). Following QuRating (Wettig et al. 2024), we introduce Edu-QuRating: a pipeline for multi-dimensional educational data scoring and curation. Edu-QuRating defines education-specific rubrics, uses an LLM judge to label sampled document pairs and distills those pairwise preferences into reusable Edu-QuRaters, which can score individual text chunks on a set of educational criteria. Across two sequence-classification base models and six educational criteria, the best Edu-QuRater recovers held-out GPT-4.1-mini pairwise judgements with mean accuracy 0.917. We then apply the resulting scorers in two applications. First, we investigate the potential of Edu-QuRaters for corpus filtering to improve pretraining of small language models. We scored 322.25M FineWeb-Edu-Fortified documents to obtain a filtered pre-training mixture. In matched single-run pre-training comparisons, models trained with Edu-QuRating-based mixtures reached higher observed aggregate accuracy across nine benchmarks than the FineWeb-Edu baseline, with gains concentrated in particular tasks. Second, we used Edu-QuRater scores as reward terms for GRPO post-training. In held-out pairwise judge evaluations, combining Edu-QuRater and answer-structure rewards produced responses preferred to the Qwen3-4B base model on both pedagogical quality and instruction following.
Authors 9
Oliver G. B. Garrod, Robin A. A. Ince, Meng Liu, Mohamed Huti, Moritz Boos, Amy Waldock, Dominic Andrews, Romana Alonso-Kropil, Paul Atherton
Specification
- Official page
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Arxiv announce type
- cross
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- arXiv id
- 2609.09425
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Categories
- cs.CL, cs.AI
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Primary category
- cs.CL
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
- Published
- 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 50 min agohigh
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Attributed facts
9
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T19
Freshest observation
50 min ago
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- Authors
- Oliver G. B. Garrod, Robin A. A. Ince, Meng Liu
As of
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Claim history · Arxiv announce type
Arxiv announce typearxiv_announce_type2
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| cross | → current | current | arXiv (Atom API + RSS)T1 | high | deterministic |
| replace | → | superseded | arXiv (Atom API + RSS)T1 | high | deterministic |
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
- Property changedPaperEdu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements
Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements: arxiv announce type changed from replace to cross
Arxiv announce typereplace→crossarxiv - New paperPaperEdu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements
New paper: Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements
arxiv
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| arXiv (Atom API + RSS) | rss.arxiv.org/rss/cs.AI | feed | T1· Official | 50 min ago | 1 |
| arXiv (Atom API + RSS) | rss.arxiv.org/rss/cs.CL | feed | T1· Official | 50 min ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.