Skip to content
← Back to explorer

HFEPX Archive Slice

HFEPX Fortnight Archive: 2025-F09

Updated from current HFEPX corpus (Mar 8, 2026). 12 papers are grouped in this daily page.

Read Full Context

Updated from current HFEPX corpus (Mar 8, 2026). 12 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Freeform. Frequently cited benchmark: PaperBench. 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 May 4, 2025.

Papers: 12 Last published: May 4, 2025 Global RSS

Researcher Quick Triage

Use this archive page for time-slice monitoring (what changed in evaluation methods, metrics, and protocol quality this period). Quality band: Medium .

High-Signal Coverage

100.0%

12 / 12 papers are not low-signal flagged.

Benchmark Anchors

0.0%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

41.7%

Papers with reported metric mentions in extraction output.

  • 0 papers report explicit quality controls for this archive period.
  • Prioritize papers with both benchmark and metric anchors for reliable longitudinal comparisons.

Primary action: Use this slice as early signal only; benchmark/metric anchoring is limited for rigorous period-over-period claims.

Why This Time Slice Matters

  • 8.3% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 41.7% of papers in this hub.
  • PaperBench is a recurring benchmark anchor for cross-paper comparisons in this page.

Protocol Takeaways For This Period

  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Rater context is mostly domain experts, and annotation is commonly Freeform; use this to scope replication staffing.
  • Track metric sensitivity by reporting both accuracy and hit@5.

Start Here (Highest-Signal Papers In This Slice)

Ranked by protocol completeness and evidence density for faster period-over-period review.

Protocol Matrix (Top 10)

Quickly compare method ingredients across this archive slice.

Paper Eval Modes Benchmarks Metrics Quality Controls
Toward Safe and Human-Aligned Game Conversational Recommendation via Multi-Agent Decomposition

Apr 26, 2025

Automatic Metrics Not reported Hit@5 Not reported
Reshaping MOFs text mining with a dynamic multi-agents framework of large language model

Apr 26, 2025

Automatic Metrics Not reported Accuracy, Precision Not reported
Reason Like a Radiologist: Chain-of-Thought and Reinforcement Learning for Verifiable Report Generation

Apr 25, 2025

Automatic Metrics Not reported Rouge Not reported
How much does context affect the accuracy of AI health advice?

Apr 25, 2025

Automatic Metrics Not reported Accuracy Not reported
ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guarantees

Apr 22, 2025

Automatic Metrics Not reported Accuracy Not reported
Adaptive Social Learning via Mode Policy Optimization for Language Agents

May 4, 2025

Simulation Env Not reported Not reported Not reported
Decoding Open-Ended Information Seeking Goals from Eye Movements in Reading

May 4, 2025

Not reported Not reported Not reported Not reported
Large Language Model Compression with Global Rank and Sparsity Optimization

May 2, 2025

Not reported Not reported Not reported Not reported
A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage

Apr 28, 2025

Not reported Not reported Not reported Not reported
FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation

Apr 24, 2025

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (8.3% vs 45% target).

  • Gap: Papers reporting quality controls

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

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (8.3% vs 35% target).

  • Moderate: Papers naming evaluation metrics

    Coverage is usable but incomplete (25% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (16.7% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (16.7% vs 35% target).

Strengths

  • This hub still surfaces a concentrated paper set for protocol triage and replication planning.

Known Gaps

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (16.7% coverage).
  • Annotation unit is under-specified (16.7% coverage).

Suggested Next Analyses

  • Track metric sensitivity by reporting both accuracy and hit@5.

Recommended Queries

Known Limitations
  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (16.7% coverage).
  • Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.
Research Utility Snapshot (Detailed)

Evaluation Modes

  • Automatic Metrics (5)
  • Simulation Env (1)

Top Metrics

  • Accuracy (2)
  • Hit@5 (1)
  • Precision (1)

Top Benchmarks

  • PaperBench (1)

Quality Controls

Papers In This Archive Slice

Recent Archive Slices

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