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Pair2Score framework transfers LLM pairwise comparisons to absolute essay scoring

By PulseAugur Editorial · Summary by gemini-2.5-flash-lite from 2 sources

Researchers have developed Pair2Score, a novel framework designed to improve the accuracy of LLM-based essay scoring by transferring knowledge from pairwise comparisons to absolute scoring. This two-stage process adapts LLaMA models, first training a ranker on comparative data and then an absolute predictor. The method shows promise in enhancing scoring metrics like quadratic weighted kappa for traits such as grammar and vocabulary, though careful configuration is needed to ensure benefits. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Introduces a new method for improving LLM-based scoring accuracy, potentially benefiting automated grading systems.

RANK_REASON This is a research paper detailing a new framework for LLM-based essay scoring.

Read on arXiv cs.CL →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 · \.Ibrahim R{\i}za Halla\c{c}, Hasan O\u{g}ul ·

    Pair2Score: Pairwise-to-Absolute Transfer for LLM-Based Essay Scoring

    arXiv:2605.02069v1 Announce Type: new Abstract: Many scoring applications require absolute predictions, while pairwise comparisons can provide a simpler learning objective. We present Pair2Score, a two-stage learning framework that transfers pairwise comparisons into absolute sco…

  2. arXiv cs.CL TIER_1 · Hasan Oğul ·

    Pair2Score: Pairwise-to-Absolute Transfer for LLM-Based Essay Scoring

    Many scoring applications require absolute predictions, while pairwise comparisons can provide a simpler learning objective. We present Pair2Score, a two-stage learning framework that transfers pairwise comparisons into absolute scoring with parameter-efficient LLaMA adaptation. …

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