assessment_design
A Judge Should Know What Changed:Construct Validity for LLM-as-a-Judge Evaluation
Jianlin Chen, Wenhui Chen, Ziyao Lin, Chi Man Vong · arXiv (2026) · doi:10.48550/arxiv.2608.24419 · gemini-3.1-flash-lite
Papers tagged with: #валідність-конструкту
psychometric_modeling
Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory
Junhyuk Choi, Sohhyung Park, Chanhee Cho, Hyeonchu Park, Bugeun Kim · arXiv (2026) · doi:10.48550/arxiv.2602.00521 · gemini-3.7-flash
psychometric_modeling
Interpretable, Fairly Evaluated Automated L2 Speaking Assessment that Beats the Single-Human Ceiling and Why Pause Encoding Does Not Change LLM Fluency Scores
Eichi Uehara · arXiv (2026) · doi:10.48550/arxiv.2608.26137 · gemini-3.8-flash
assessment_design
Rubrics Carry the Standard: Shapley Attribution for Checklist-Based LLM Judges
Saeid Asgari, Rui Ying, Sara Malvar, Rakshanda Agarwal, Bruce Sun, Claire Wang, Leonardo de Oliveira Nunes, Ranveer Chandra · arXiv (2026) · doi:10.48550/arxiv.2610.24971 · gemini-3.8-flash
psychometric_modeling
Inside the Scorer: Mechanistic Evidence on Rubric Control in LLM-Based Automated Essay Scoring from 25 Base Models
Chungche Huang, Po-Ya Angela Wang, Shu-Kai Hsieh · arXiv (2026) · doi:10.48550/arxiv.2610.25724 · gemini-3.7-flash