[2605.11242] RETUYT-INCO at BEA 2026 Shared Task 2: Meta-prompting in Rubric-based Scoring for German
[Submitted on 11 May 2026]
Title:RETUYT-INCO at BEA 2026 Shared Task 2: Meta-prompting in Rubric-based Scoring for German
View a PDF of the paper titled RETUYT-INCO at BEA 2026 Shared Task 2: Meta-prompting in Rubric-based Scoring for German, by Ignacio Sastre and 5 other authors
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Abstract:In this paper, we present the RETUYT-INCO participation at the BEA 2026 shared task "Rubric-based Short Answer Scoring for German". Our team participated in track 1 (Unseen answers three-way), track 3 (Unseen answers two-way) and track 4 (Unseen questions two-way). Since these tracks required scoring short student answers using specific rubrics, we looked for ways to handle the changing nature of the task. We created a method called Meta-prompting. In this approach, an LLM creates a custom prompt based on examples from the Train set. This prompt is then used to grade new student answers. Along with this method, we also describe other approaches we used, such as classic machine learning, fine-tuning open-source LLMs, and different prompting techniques. According to the official results, our team placed 6th out of 8 participants in Track 1 with a QWK of 0.729. In Track 3, we secured 4th place out of 9 with a QWK of 0.674, and we also placed 4th out of 8 in Track 4 with a QWK of 0.49.
Comments: To be presented at the BEA 2026 workshop, co-located with ACL 2026
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2605.11242 [cs.CL]
(or arXiv:2605.11242v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2605.11242
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Santiago Góngora [view email] [v1] Mon, 11 May 2026 21:01:05 UTC (61 KB)
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