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HFEPX Archive Slice

HFEPX Weekly Archive: 2026-W07

Updated from current HFEPX corpus (Apr 12, 2026). 152 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 152 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Trajectory. Frequent quality control: Calibration. Frequently cited benchmark: BrowseComp. 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 Feb 15, 2026.

Papers: 152 Last published: Feb 15, 2026 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: High .

Analysis blocks are computed from the loaded sample (60 of 152 papers).

High-Signal Coverage

100.0%

60 / 60 papers are not low-signal flagged.

Benchmark Anchors

20.0%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

55.0%

Papers with reported metric mentions in extraction output.

  • 3 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 for trend comparison: review top papers first, then validate shifts in the protocol matrix.

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Why This Time Slice Matters

  • 18.4% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 34.9% of papers in this hub.
  • BrowseComp is a recurring benchmark anchor for cross-paper comparisons in this page.

Protocol Takeaways For This Period

  • Most common quality-control signal is rater calibration (2.6% of papers).
  • Rater context is mostly domain experts, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.
  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.

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
HLE-Verified: A Systematic Verification and Structured Revision of Humanity's Last Exam

Feb 15, 2026

Automatic Metrics HLE Accuracy Adjudication
AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents

Feb 15, 2026

Simulation Env Ad Bench Pass@1, Pass@3 Not reported
MAGE: All-[MASK] Block Already Knows Where to Look in Diffusion LLM

Feb 15, 2026

Automatic Metrics LongBench, Needle In A Haystack Accuracy, Cost Not reported
The Sufficiency-Conciseness Trade-off in LLM Self-Explanation from an Information Bottleneck Perspective

Feb 15, 2026

Automatic Metrics ARC Challenge Accuracy, Conciseness Not reported
Neuromem: A Granular Decomposition of the Streaming Lifecycle in External Memory for LLMs

Feb 15, 2026

Automatic Metrics Insertion And Retrieval, Longmemeval Accuracy, F1 Not reported
Pre-Editorial Normalization for Automatically Transcribed Medieval Manuscripts in Old French and Latin

Feb 14, 2026

Automatic Metrics Medieval Cer Not reported
Do Mixed-Vendor Multi-Agent LLMs Improve Clinical Diagnosis?

Feb 14, 2026

Automatic Metrics Rarebench, Diagnosisarena Accuracy, Recall Not reported
LM-Lexicon: Improving Definition Modeling via Harmonizing Semantic Experts

Feb 15, 2026

Automatic Metrics Not reported Bleu Not reported
From Pixels to Policies: Reinforcing Spatial Reasoning in Language Models for Content-Aware Layout Design

Feb 14, 2026

Simulation Env Not reported Latency Not reported
ADAB: Arabic Dataset for Automated Politeness Benchmarking -- A Large-Scale Resource for Computational Sociopragmatics

Feb 14, 2026

Automatic Metrics Not reported Kappa, Agreement Inter Annotator Agreement Reported
Researcher Workflow (Detailed)

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (18.4% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (4.6% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (11.8% vs 35% target).

  • Moderate: Papers naming evaluation metrics

    Coverage is usable but incomplete (27% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (11.2% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (18.4% vs 35% target).

Strengths

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

Known Gaps

  • Only 4.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (11.2% coverage).
  • Annotation unit is under-specified (18.4% coverage).

Suggested Next Analyses

  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Stratify by benchmark (BrowseComp vs MT-Bench) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.

Recommended Queries

Known Limitations
  • Only 4.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (11.2% 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 (53)
  • Simulation Env (7)
  • Llm As Judge (3)

Top Metrics

  • Accuracy (19)
  • Cost (7)
  • Latency (5)
  • Relevance (3)

Top Benchmarks

  • BrowseComp (2)
  • MT Bench (2)
  • Ad Bench (1)
  • Agent Diff Bench (1)

Quality Controls

  • Calibration (4)
  • Inter Annotator Agreement Reported (2)
  • Adjudication (1)

Papers In This Archive Slice

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