arXiv (All)
open access
Rubric Spans are Label Representations: Joint LLM Encoding for Short Answer Scoring
Automatic Short Answer Scoring (ASAS) requires models that can score student responses against question-specific criteria while remaining efficient and transferable across rubric sets. We propose RUSPAN, a rubric-conditioned ASAS framework that treats rubric descriptions as semantic label representa
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Alice: A Large-Scale German Benchmark for Rubric-Based Multi-Dimensional Automatic Short Answer Scoring#1234028
- TeachGrade: Training-Free Short Answer Scoring with Teacher Evidence#1325796
- Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring#151722
- MATA: Mindful Assessment of the Telugu Abilities of Large Language Models#819243
- MATA: Mindful Assessment of the Telugu Abilities of Large Language Models#809251
Record · ID 1234027
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive