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HFEPX Metric Hub

Coherence + General Metric Papers

Updated from current HFEPX corpus (Apr 12, 2026). 15 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Apr 12, 2026). 15 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Llm As Judge. Common annotation unit: Trajectory. Frequently cited benchmark: ALFWorld. Common metric signal: coherence. 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 Apr 9, 2026.

Papers: 15 Last published: Apr 9, 2026 Global RSS

When This Metric Page Is Useful

Useful for background comparison, but still validate benchmark and protocol details in the linked papers. Quality band: Medium .

Metric Coverage

93.3%

14 sampled papers include metric names.

Benchmark Anchoring

26.7%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

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

Recommended next step: Treat this as directional signal only; metric reporting is present but benchmark anchoring is still thin.

Main limitation: Benchmark coverage is still thin, so avoid treating this page as a definitive guide to the metric.

What This Metric Page Tells You

What This Metric Page Tells You

  • 40% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 60% of papers in this hub.
  • ALFWorld is a recurring benchmark anchor for cross-paper comparisons in this page.
Metric Notes (Expanded)

Metric-Driven Protocol Takeaways

  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Rater context is mostly unspecified rater pools, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.
  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.

Metric Interpretation

  • coherence is reported in 100% of hub papers (15/15); compare with a secondary metric before ranking methods.
  • accuracy is reported in 20% of hub papers (3/15); compare with a secondary metric before ranking methods.

Benchmark Context

  • ALFWorld appears in 6.7% of hub papers (1/15); use this cohort for benchmark-matched comparisons.
  • MLE-Bench appears in 6.7% of hub papers (1/15); 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
$\texttt{YC-Bench}$: Benchmarking AI Agents for Long-Term Planning and Consistent Execution

Apr 1, 2026

Cost, Inference cost Yc Bench Automatic Metrics Not reported
HyperMem: Hypergraph Memory for Long-Term Conversations

Apr 9, 2026

Accuracy, Coherence Not reported Llm As Judge, Automatic Metrics Not reported
Embodied Task Planning via Graph-Informed Action Generation with Large Language Model

Jan 29, 2026

Pass@1, Cost ALFWorld Simulation Env Not reported
PLOT: Enhancing Preference Learning via Optimal Transport

Apr 2, 2026

Coherence Not reported Automatic Metrics Not reported
BeliefShift: Benchmarking Temporal Belief Consistency and Opinion Drift in LLM Agents

Mar 25, 2026

Accuracy, Coherence Not reported Automatic Metrics Not reported
QChunker: Learning Question-Aware Text Chunking for Domain RAG via Multi-Agent Debate

Mar 12, 2026

Coherence Understanding Retrieval Automatic Metrics Not reported
VRM: Teaching Reward Models to Understand Authentic Human Preferences

Mar 5, 2026

Coherence Not reported Human Eval Not reported
The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration

Oct 30, 2025

Accuracy, Coherence Not reported Automatic Metrics Not reported
Reasoning or Rhetoric? An Empirical Analysis of Moral Reasoning Explanations in Large Language Models

Mar 23, 2026

Coherence Not reported Llm As Judge Not reported
Discourse Coherence and Response-Guided Context Rewriting for Multi-Party Dialogue Generation

Apr 8, 2026

Coherence Not reported Not reported Not reported
How To Use This Page

Checklist

  • Moderate: Papers with explicit human feedback

    Coverage is usable but incomplete (40% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (0% vs 30% target).

  • Moderate: Papers naming benchmarks/datasets

    Coverage is usable but incomplete (26.7% vs 35% target).

  • Strong: Papers naming evaluation metrics

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

  • Gap: Papers with known rater population

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

  • Strong: Papers with known annotation unit

    Coverage is strong (46.7% vs 35% target).

Strengths

  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.
  • Agentic evaluation appears in 60% of papers.

Known Gaps

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (0% coverage).
  • LLM-as-judge appears without enough inter-annotator agreement reporting.

Suggested Next Analyses

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

Recommended Queries

Known Limitations
  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (0% coverage).
  • Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.
Coverage Snapshot

Top Metrics

  • Coherence (15)
  • Accuracy (3)
  • Cost (2)
  • Inference cost (1)

Evaluation Modes

  • Automatic Metrics (9)
  • Llm As Judge (3)
  • Simulation Env (3)
  • Human Eval (1)

Top Benchmarks

  • ALFWorld (1)
  • MLE Bench (1)
  • Understanding Retrieval (1)
  • Yc Bench (1)

Agentic Mix

  • Long Horizon (6)
  • Multi Agent (3)

Top Papers Reporting This Metric

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