- LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias
Filip J. Kucia, Anirban Chakraborty, Anna Wróblewska · Mar 31, 2026 · Citations: 0
Rubric Rating Human Eval
We present a systematic evaluation of instruction-tuned LLMs across three open essay-scoring datasets (ASAP 2.0, ELLIPSE, and DREsS) that cover both holistic and analytic scoring.
- Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
Qiyao Ma, Dechen Gao, Rui Cai, Boqi Zhao, Hanchu Zhou · Apr 8, 2026 · Citations: 0
Pairwise PreferenceRubric Rating Human EvalAutomatic Metrics
Pluralistic alignment has emerged as a critical frontier in the development of Large Language Models (LLMs), with reward models (RMs) serving as a central mechanism for capturing diverse human values.
- More Human, More Efficient: Aligning Annotations with Quantized SLMs
Jiayu Wang, Junyoung Lee · Apr 1, 2026 · Citations: 0
Rubric Rating Automatic Metrics
As Large Language Model (LLM) capabilities advance, the demand for high-quality annotation of exponentially increasing text corpora has outpaced human capacity, leading to the widespread adoption of LLMs in automatic evaluation and…
- Beyond the Illusion of Consensus: From Surface Heuristics to Knowledge-Grounded Evaluation in LLM-as-a-Judge
Mingyang Song, Mao Zheng, Chenning Xu · Mar 11, 2026 · Citations: 0
Rubric RatingCritique Edit Llm As Judge
Through a large-scale study of 105,600 evaluation instances (32 LLMs \times 3 frontier judges \times 100 tasks \times 11 temperatures), we show that model-level agreement (Spearman ρ= 0.99) masks fragile sample-level agreement (Pearson r =…
- Evaluating Austrian A-Level German Essays with Large Language Models for Automated Essay Scoring
Jonas Kubesch, Lena Huber, Clemens Havas · Mar 6, 2026 · Citations: 0
Rubric Rating Human Eval
This paper investigates the application of state-of-the-art open-weight LLMs for the grading of Austrian A-level German texts, with a particular focus on rubric-based evaluation.
- Beyond Paper-to-Paper: Structured Profiling and Rubric Scoring for Paper-Reviewer Matching
Yicheng Pan, Zhiyuan Ning, Ludi Wang, Yi Du · Apr 7, 2026 · Citations: 0
Rubric Rating Automatic Metrics
To address this gap, we propose P2R, a training-free framework that shifts from implicit paper-to-paper matching to explicit profile-based matching.
- When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools
Xingming Li, Runke Huang, Yanan Bao, Yuye Jin, Yuru Jiao · Mar 25, 2026 · Citations: 0
Rubric Rating Automatic Metrics
In this paper, we investigate whether AI can serve as a scalable assessment teammate by extracting structured quality indicators and validating their alignment with human expert judgments.
- I Can't Believe It's Corrupt: Evaluating Corruption in Multi-Agent Governance Systems
Vedanta S P, Ponnurangam Kumaraguru · Mar 19, 2026 · Citations: 0
Rubric Rating Simulation Env Multi Agent
Large language models are increasingly proposed as autonomous agents for high-stakes public workflows, yet we lack systematic evidence about whether they would follow institutional rules when granted authority.
- Rethinking Atomic Decomposition for LLM Judges: A Prompt-Controlled Study of Reference-Grounded QA Evaluation
Xinran Zhang · Mar 30, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Atomic decomposition -- breaking a candidate answer into claims before verifying each against a reference -- is a widely adopted design for LLM-based reference-grounded judges.
- Stabilizing Rubric Integration Training via Decoupled Advantage Normalization
Zelin Tan, Zhouliang Yu, Bohan Lin, Zijie Geng, Hejia Geng · Mar 27, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We propose Process-Aware Policy Optimization (PAPO), a method that integrates process-level evaluation into Group Relative Policy Optimization (GRPO) through decoupled advantage normalization, to address two limitations of existing reward…
- CHiL(L)Grader: Calibrated Human-in-the-Loop Short-Answer Grading
Pranav Raikote, Korbinian Randl, Ioanna Miliou, Athanasios Lakes, Panagiotis Papapetrou · Mar 12, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We introduce CHiL(L)Grader, the first automated grading framework that incorporates calibrated confidence estimation into a human-in-the-loop workflow.
- FrontierFinance: A Long-Horizon Computer-Use Benchmark of Real-World Financial Tasks
Michael Krumdick, Varshini Reddy, Shivani Chaudhary, William Day, Maarij Ahmed · Apr 7, 2026 · Citations: 0
Rubric Rating Long Horizon
To address this, we introduce FrontierFinance, a long-horizon benchmark of 25 complex financial modeling tasks across five core finance models, requiring an average of over 18 hours of skilled human labor per task to complete.
- EvoIdeator: Evolving Scientific Ideas through Checklist-Grounded Reinforcement Learning
Andreas Sauter, Yuyue Zhao, Jacopo Urbani, Wenxiang Hu, Zaiqiao Meng · Mar 23, 2026 · Citations: 0
Rubric RatingCritique Edit Llm As Judge
EvoIdeator leverages a structured judge model to generate two synergistic signals: (1) lexicographic rewards for multi-dimensional optimization, and (2) fine-grained language feedback that offers span-level critiques regarding grounding,…
- Decision-Level Ordinal Modeling for Multimodal Essay Scoring with Large Language Models
Han Zhang, Jiamin Su, Li liu · Mar 16, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Experiments on the multimodal EssayJudge dataset show that DLOM improves over a generation-based SFT baseline across scoring traits, and DLOM-GF yields further gains when modality relevance is heterogeneous.
- MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome
Fangda Ye, Yuxin Hu, Pengxiang Zhu, Yibo Li, Ziqi Jin · Mar 30, 2026 · Citations: 0
Rubric Rating
Recent progress in deep research systems has been impressive, but evaluation still lags behind real user needs.
- Training data generation for context-dependent rubric-based short answer grading
Pavel Šindelář, Dávid Slivka, Christopher Bouma, Filip Prášil, Ondřej Bojar · Mar 30, 2026 · Citations: 0
Rubric Rating
However, having to avoid language differences and annotator bias makes the grading of student answers challenging.