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HFEPX Metric Hub

Accuracy + Coding Metric Papers (Last 90 Days)

Updated from current HFEPX corpus (Mar 1, 2026). 11 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Mar 1, 2026). 11 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Trajectory. Frequent quality control: Gold Questions. Frequently cited benchmark: BIRD. Common metric signal: accuracy. 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 Dec 26, 2025.

Papers: 11 Last published: Dec 26, 2025 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

100.0%

11 sampled papers include metric names.

Benchmark Anchoring

9.1%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

9.1%

1 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

  • 27.3% of papers report explicit human-feedback signals, led by expert verification.
  • automatic metrics appears in 100% of papers in this hub.
  • BIRD is a recurring benchmark anchor for cross-paper comparisons in this page.
Metric Notes (Expanded)

Metric-Driven Protocol Takeaways

  • Most common quality-control signal is gold-question checks (9.1% of papers).
  • Rater context is mostly domain experts, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.
  • Stratify by benchmark (BIRD vs Cricbench) before comparing methods.

Metric Interpretation

  • accuracy is reported in 100% of hub papers (11/11); compare with a secondary metric before ranking methods.
  • cost is reported in 18.2% of hub papers (2/11); compare with a secondary metric before ranking methods.

Benchmark Context

  • BIRD appears in 9.1% of hub papers (1/11); use this cohort for benchmark-matched comparisons.
  • Cricbench appears in 9.1% of hub papers (1/11); 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
CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics

Dec 26, 2025

 Accuracy DROP, BIRD Automatic Metrics Gold Questions
MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models

Feb 25, 2026

 Accuracy Not reported Automatic Metrics Not reported
SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video

Feb 25, 2026

 Accuracy Not reported Automatic Metrics Not reported
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching

Feb 26, 2026

 Accuracy, Latency Not reported Automatic Metrics Not reported
Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics

Feb 23, 2026

 Accuracy, Cost Not reported Automatic Metrics Not reported
AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning

Feb 26, 2026

 Accuracy Not reported Automatic Metrics Not reported
AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG

Feb 22, 2026

 Accuracy Not reported Automatic Metrics Not reported
Counterfactual Simulation Training for Chain-of-Thought Faithfulness

Feb 24, 2026

 Accuracy, Faithfulness Not reported Automatic Metrics, Simulation Env Not reported
GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

Feb 25, 2026

 Accuracy, Task success Not reported Automatic Metrics Not reported
Classroom Final Exam: An Instructor-Tested Reasoning Benchmark

Feb 23, 2026

 Accuracy Not reported Automatic Metrics Not reported
Researcher Workflow (Detailed)

Checklist

  • Moderate: Papers with explicit human feedback

    Coverage is usable but incomplete (27.3% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (9.1% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (9.1% vs 35% target).

  • Strong: Papers naming evaluation metrics

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

  • Strong: Papers with known rater population

    Coverage is strong (36.4% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (18.2% vs 35% target).

Strengths

  • Agentic evaluation appears in 54.5% of papers.

Known Gaps

  • Only 9.1% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Annotation unit is under-specified (18.2% coverage).
  • Benchmark coverage is thin (9.1% of papers mention benchmarks/datasets).

Suggested Next Analyses

  • Stratify by benchmark (BIRD vs Cricbench) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.
  • Add inter-annotator agreement checks when reproducing these protocols.

Recommended Queries

Benchmark Slice: BIRDMetric Slice: accuracyRecent High-Signal Papers
Known Limitations
  • Only 9.1% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Annotation unit is under-specified (18.2% coverage).
  • Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.
Research Utility Snapshot (Detailed)

Top Metrics

  • Accuracy (11)
  • Cost (2)
  • Faithfulness (1)
  • Latency (1)

Evaluation Modes

  • Automatic Metrics (11)
  • Simulation Env (2)

Top Benchmarks

  • BIRD (1)
  • Cricbench (1)
  • DROP (1)

Agentic Mix

  • Long Horizon (5)
  • Multi Agent (1)
  • Web Browsing (1)

Top Papers Reporting This Metric

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