Skip to content
← Back to explorer

HFEPX Metric Hub

Kappa In CS.CL Papers

Updated from current HFEPX corpus (Apr 11, 2026). 11 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Apr 11, 2026). 11 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Human Eval. Most common rater population: Domain Experts. Common annotation unit: Pairwise. Frequent quality control: Inter Annotator Agreement Reported. Common metric signal: kappa. 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: 11 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

63.6%

7 sampled papers include metric names.

Benchmark Anchoring

0.0%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

63.6%

7 papers report calibration/adjudication/IAA controls.

  • 11 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

  • 85.7% of papers report explicit human-feedback signals, led by expert verification.
  • automatic metrics appears in 54.5% of papers in this hub.
  • long-horizon tasks appears in 9.1% of papers, indicating agentic evaluation demand.
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 (54.5% of papers).
  • Rater context is mostly domain experts, and annotation is commonly pairwise annotation; use this to scope replication staffing.

Metric Interpretation

  • kappa is reported in 100% of hub papers (7/11); compare with a secondary metric before ranking methods.
  • accuracy is reported in 57.1% of hub papers (4/11); compare with a secondary metric before ranking methods.

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
From Consensus to Split Decisions: ABC-Stratified Sentiment in Holocaust Oral Histories

Mar 30, 2026

 Kappa, Agreement Not reported Automatic Metrics Inter Annotator Agreement Reported
SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model

Mar 22, 2026

 Accuracy, Kappa Not reported Automatic Metrics Inter Annotator Agreement Reported
Measuring Faithfulness Depends on How You Measure: Classifier Sensitivity in LLM Chain-of-Thought Evaluation

Mar 20, 2026

 Kappa, Faithfulness Not reported Automatic Metrics Inter Annotator Agreement Reported
From Days to Minutes: An Autonomous AI Agent Achieves Reliable Clinical Triage in Remote Patient Monitoring

Mar 10, 2026

 Accuracy, Kappa Not reported Automatic Metrics Adjudication
Personalized Prediction of Perceived Message Effectiveness Using Large Language Model Based Digital Twins

Feb 23, 2026

 Accuracy, F1 Not reported Automatic Metrics Inter Annotator Agreement Reported
Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith

Mar 25, 2026

 Accuracy, Kappa Not reported Human Eval, Llm As Judge Inter Annotator Agreement Reported
IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures

Apr 9, 2026

 Not reported Not reported Not reported Not reported
Swiss-Bench SBP-002: A Frontier Model Comparison on Swiss Legal and Regulatory Tasks

Mar 24, 2026

 Not reported Not reported Not reported Not reported
Interpretable Chinese Metaphor Identification via LLM-Assisted MIPVU Rule Script Generation: A Comparative Protocol Study

Mar 11, 2026

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

Checklist

  • Strong: Papers with explicit human feedback

    Coverage is strong (85.7% vs 45% target).

  • Strong: Papers reporting quality controls

    Coverage is strong (100% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (0% vs 35% target).

  • Strong: Papers naming evaluation metrics

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

  • Moderate: Papers with known rater population

    Coverage is usable but incomplete (28.6% vs 35% target).

  • Strong: Papers with known annotation unit

    Coverage is strong (57.1% vs 35% target).

Strengths

  • Strong human-feedback signal (85.7% of papers).
  • Quality-control evidence appears in 100% of papers.
  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.

Known Gaps

  • Benchmark coverage is thin (0% of papers mention benchmarks/datasets).

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Track metric sensitivity by reporting both kappa and accuracy.

Recommended Queries

Judge vs Human AgreementMetric Slice: kappaIAA-Reported EvaluationsRecent High-Signal Papers
Known Limitations
  • Benchmark coverage is thin (0% of papers mention benchmarks/datasets).
  • 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

  • Kappa (7)
  • Accuracy (4)
  • Agreement (3)
  • Coherence (1)

Evaluation Modes

  • Automatic Metrics (6)
  • Human Eval (2)
  • Llm As Judge (1)

Top Benchmarks

Agentic Mix

  • Long Horizon (1)

Top Papers Reporting This Metric

Related Metric Hubs

Kappa Metric Papers Agreement & Reliability Metric Papers In CS.CL Agreement & Reliability Metric Papers CS.CL Papers (Last 60 Days) CS.CL Papers (Last 90 Days) CS.CL Human Feedback And Eval Papers Coherence + General Metric Papers (Last 120 Days) (12) Coherence + General Metric Papers (Last 60 Days) (10) Coherence + General Metric Papers (Last 90 Days) (12) Coherence + General Metric Papers (15) Helpfulness In CS.CL Papers (12) Helpfulness Metric Papers (15) Relevance + Automatic Metrics Metric Papers (Last 120 Days) (18) Relevance + Automatic Metrics Metric Papers (Last 45 Days) (14) Relevance + Automatic Metrics Metric Papers (Last 60 Days) (16) Relevance + Automatic Metrics Metric Papers (Last 90 Days) (17) Relevance + Automatic Metrics Metric Papers (22) Relevance + General Metric Papers (Last 120 Days) (11) Relevance + General Metric Papers (Last 45 Days) (10) Relevance + General Metric Papers (Last 60 Days) (11) Relevance + General Metric Papers (Last 90 Days) (11) Relevance + General Metric Papers (12) Relevance + Pairwise Preference Metric Papers (Last 120 Days) (10) Relevance + Pairwise Preference Metric Papers (11)

Need human evaluators for your AI research? Scale annotation with expert AI Trainers.

Post a Job Get a Quote