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HFEPX Metric Hub

Agreement + Rubric Rating Metric Papers

Updated from current HFEPX corpus (Apr 5, 2026). 10 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Apr 5, 2026). 10 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Human Eval. Most common rater population: Domain Experts. Common annotation unit: Multi Dim Rubric. Frequent quality control: Inter Annotator Agreement Reported. Frequently cited benchmark: Healthbench. Common metric signal: agreement. Use this page to compare protocol setup, judge behavior, and labeling design decisions before running new eval experiments. Newest paper in this set is from Mar 31, 2026.

Papers: 10 Last published: Mar 31, 2026 Global RSS

Researcher Quick Triage

Use this page to compare metric behavior across protocols and benchmarks before selecting your reporting stack. Quality band: Developing .

Metric Coverage

90.0%

9 sampled papers include metric names.

Benchmark Anchoring

20.0%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

50.0%

5 papers report calibration/adjudication/IAA controls.

  • 10 papers are not low-signal flagged in this sample.
  • Use the protocol matrix below to avoid comparing metrics across incompatible eval setups.

Primary action: Treat this as directional signal only; metric reporting is present but benchmark anchoring is still thin.

Why This Matters (Expanded)

Why This Matters For Eval Research

  • 100% of papers report explicit human-feedback signals, led by rubric ratings.
  • automatic metrics appears in 50% of papers in this hub.
  • Healthbench is a recurring benchmark anchor for cross-paper comparisons in this page.
Metric Notes (Expanded)

Metric-Driven Protocol Takeaways

  • 1 sampled papers report both human evaluation and LLM-as-judge, supporting direct agreement checks.
  • Most common quality-control signal is inter-annotator agreement reporting (50% of papers).
  • Rater context is mostly domain experts, and annotation is commonly multi-dimensional rubrics; use this to scope replication staffing.

Metric Interpretation

  • agreement is reported in 100% of hub papers (10/10); compare with a secondary metric before ranking methods.
  • accuracy is reported in 20% of hub papers (2/10); compare with a secondary metric before ranking methods.

Benchmark Context

  • Healthbench appears in 10% of hub papers (1/10); use this cohort for benchmark-matched comparisons.
  • Interaction2eval appears in 10% of hub papers (1/10); use this cohort for benchmark-matched comparisons.

Start Here (Metric-Reliable First 6)

Ranked for metric reporting completeness and comparability.

Metric Protocol Matrix (Top 10)

Compare metric, benchmark, and evaluation context side by side.

Paper Metrics Benchmarks Eval Modes Quality Controls
LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias

Mar 31, 2026

Kappa, Agreement Not reported Human Eval Inter Annotator Agreement Reported, Adjudication
More Human, More Efficient: Aligning Annotations with Quantized SLMs

Apr 1, 2026

Agreement Not reported Automatic Metrics Inter Annotator Agreement Reported, Adjudication
When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools

Mar 25, 2026

Agreement, Cost Interaction2eval Automatic Metrics Not reported
From Intuition to Calibrated Judgment: A Rubric-Based Expert-Panel Study of Human Detection of LLM-Generated Korean Text

Jan 6, 2026

Accuracy, Agreement Not reported Automatic Metrics Calibration, Inter Annotator Agreement Reported
Beyond the Illusion of Consensus: From Surface Heuristics to Knowledge-Grounded Evaluation in LLM-as-a-Judge

Mar 11, 2026

Spearman Not reported Llm As Judge Not reported
MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages

Sep 30, 2025

Agreement Not reported Automatic Metrics Inter Annotator Agreement Reported
Evaluating Austrian A-Level German Essays with Large Language Models for Automated Essay Scoring

Mar 6, 2026

Agreement Not reported Human Eval Not reported
HEART: A Unified Benchmark for Assessing Humans and LLMs in Emotional Support Dialogue

Jan 9, 2026

Agreement Not reported Human Eval, Llm As Judge Not reported
A Scalable Framework for Evaluating Health Language Models

Mar 30, 2025

Accuracy, Agreement Not reported Automatic Metrics Inter Annotator Agreement Reported
Decomposing Physician Disagreement in HealthBench

Feb 26, 2026

Not reported Healthbench Not reported Not reported
Researcher Workflow (Detailed)

Checklist

  • Strong: Papers with explicit human feedback

    Coverage is strong (100% vs 45% target).

  • Strong: Papers reporting quality controls

    Coverage is strong (50% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (20% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (100% vs 35% target).

  • Strong: Papers with known rater population

    Coverage is strong (70% vs 35% target).

  • Strong: Papers with known annotation unit

    Coverage is strong (100% vs 35% target).

Strengths

  • Strong human-feedback signal (100% of papers).
  • Quality-control evidence appears in 50% of papers.
  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.

Known Gaps

  • No dominant metadata gap detected in current extraction coverage.

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Stratify by benchmark (Healthbench vs Interaction2eval) before comparing methods.
  • Track metric sensitivity by reporting both agreement and accuracy.

Recommended Queries

Known Limitations
  • No dominant metadata gap detected in current extraction coverage.
  • Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.
  • Cross-page comparisons should be benchmark- and metric-matched to avoid protocol confounding.
Research Utility Snapshot (Detailed)

Top Metrics

  • Agreement (10)
  • Accuracy (2)
  • Cost (2)
  • Kappa (1)

Evaluation Modes

  • Automatic Metrics (5)
  • Human Eval (3)
  • Llm As Judge (2)

Top Benchmarks

  • Healthbench (1)
  • Interaction2eval (1)

Agentic Mix

Top Papers Reporting This Metric

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