PsyScore-AES achieves a state-of-the-art average QWK of 0.747 on ASAP++, surpassing the strongest baseline SaMRL-large (0.722) and ranking first on 6 of 8 prompts¶
Claim · All claims
Evidence · 1 study · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
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This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? On the ASAP++ benchmark, PsyScore-AES attains an average QWK of 0.747 across prompts, exceeding SaMRL-large's 0.722 and ranking first on 6 of 8 prompts. → Wei Xia 2026
Evidence¶
Wei Xia 2026¶
Wei Xia, Jin Wu, Haoran Shi, Xiangyu Wang, Chanjin Zheng. (2026). PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback. arXiv preprint. https://arxiv.org/abs/2606.20287 doi:10.48550/arxiv.2606.20287
q2 · i? · design · r2
Benchmark comparison on the ASAP++ dataset (6:2:2 split, 5-fold ensemble of bert-base-uncased) reported in Table 1: PsyScore-AES reaches "a new state-of-the-art average Quadratic Weighted Kappa (QWK) of 0.747" versus 0.722 for SaMRL-large.
"PsyScore-AES achieves a new state-of-the-art average Quadratic Weighted Kappa (QWK) of 0.747, surpassing the strongest baseline (SaMRL-large, 0.722) and ranking first in 6 out of 8 prompts."
Discussion¶
Related Claims¶
- At trait level PsyScore-AES ranks first in 10 of 11 dimensions (mean QWK 0.735), improving Voice scoring from 0.619 to 0.740 while trailing T-MES on Style — related
- Removing grid-search initialization of IRT discrimination and difficulty parameters drops scoring performance from QWK 0.747 to 0.705 — related
- GRPO with the Proficiency Alignment Reward improves alignment over SFT across every writing trait and essay prompt — related
- Supervised fine-tuning on real score–essay pairs substantially outperforms prompting for proficiency-conditioned writing simulation — related
- Rubric-grounded prompting alone provides limited proficiency control, aligning far better on content-oriented traits than on form-oriented traits — related
- Three education experts rate PsyScore feedback significantly higher than all LLM baselines on every dimension (p < .001), with the No-IRT ablation declining in Adaptivity and Accuracy (p < .05) — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
psyscore-aes-sota-qwk-0-747-asap |
title |
PsyScore-AES achieves a state-of-the-art average QWK of 0.747 on ASAP++, surpassing the strongest baseline SaMRL-large (0.722) and ranking first on 6 of 8 prompts |
description |
PsyScore-AES achieves a state-of-the-art average QWK of 0.747 on ASAP++, surpassing the strongest baseline SaMRL-large (0.722) and ranking first on 6 of 8 prompts |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — wei-xia-2026 |
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