LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias
LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias explores An LLM-based essay scoring system that identifies and corrects systematic biases in grading, improving accuracy with minimal data.. Commercial viability score: 7/10 in LLM Applications.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMeasuring What Matters -- or What's Convenient?: Robustness of LLM-Based Scoring Systems to Construct-Irrelevant FactorsViability: 4.0
- Builds On ThisUnderstanding LLM Evaluator Behavior: A Structured Multi-Evaluator Framework for Merchant Risk AssessmentViability: 3.0
- Builds On ThisComparing Developer and LLM Biases in Code EvaluationViability: 4.0
- Builds On ThisSame Meaning, Different Scores: Lexical and Syntactic Sensitivity in LLM EvaluationViability: 4.0
- Prior WorkImplicit Grading Bias in Large Language Models: How Writing Style Affects Automated Assessment Across Math, Programming, and Essay Tasks
Related Resources
- What are the best practices for implementing causal prompt optimization in enterprise LLM applications?(question)
- How does modality-aware scheduling in RPS-Serve help with multimodal LLM applications?(question)
- How can AI infrastructure be optimized for real-time LLM applications requiring low latency?(question)