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HFEPX Archive Slice

HFEPX Weekly Archive: 2025-W09

Updated from current HFEPX corpus (Apr 17, 2026). 22 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 17, 2026). 22 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Llm As Judge. Most common rater population: Domain Experts. Common annotation unit: Pairwise. Frequent quality control: Calibration. 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 28, 2025.

Papers: 22 Last published: Feb 28, 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: High .

High-Signal Coverage

100.0%

22 / 22 papers are not low-signal flagged.

Benchmark Anchors

9.1%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

40.9%

Papers with reported metric mentions in extraction output.

  • 1 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.

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Why This Time Slice Matters

  • 13.6% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 36.4% of papers in this hub.
  • multi-agent setups appears in 9.1% of papers, indicating agentic evaluation demand.

Protocol Takeaways For This Period

  • Most common quality-control signal is rater calibration (4.5% of papers).
  • Rater context is mostly domain experts, and annotation is commonly pairwise 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
PII-Bench: Evaluating Query-Aware Privacy Protection Systems

Feb 25, 2025

Automatic Metrics Pii Bench Relevance Not reported
Compressing Language Models for Specialized Domains

Feb 25, 2025

Automatic Metrics Not reported Cost Calibration
Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking Attacks

Feb 28, 2025

Not reported Not reported Helpfulness Not reported
Prediction of Item Difficulty for Reading Comprehension Items by Creation of Annotated Item Repository

Feb 28, 2025

Automatic Metrics Not reported Rmse Not reported
HaLoRA: Hardware-aware Low-Rank Adaptation for Large Language Models Based on Hybrid Compute-in-Memory Architecture

Feb 27, 2025

Automatic Metrics Not reported Accuracy, Cost Not reported
Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization

Feb 25, 2025

Automatic Metrics Not reported Accuracy Not reported
Unveiling Downstream Performance Scaling of LLMs: A Clustering-Based Perspective

Feb 24, 2025

Automatic Metrics Not reported Accuracy, Cost Not reported
Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence

Feb 24, 2025

Automatic Metrics Not reported Not reported Not reported
Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning

Feb 26, 2025

Not reported MT Bench Not reported Not reported
Connecting Voices: LoReSpeech as a Low-Resource Speech Parallel Corpus

Feb 25, 2025

Not reported Not reported Jailbreak success rate Not reported
Researcher Workflow (Detailed)

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (13.6% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (4.5% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

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

  • Gap: Papers naming evaluation metrics

    Coverage is a replication risk (13.6% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (13.6% vs 35% target).

  • Gap: Papers with known annotation unit

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

Strengths

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

Known Gaps

  • Only 4.5% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (13.6% coverage).
  • Annotation unit is under-specified (9.1% coverage).

Suggested Next Analyses

  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Track metric sensitivity by reporting both accuracy and helpfulness.
  • Add inter-annotator agreement checks when reproducing these protocols.

Recommended Queries

Known Limitations
  • Only 4.5% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (13.6% 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 (8)
  • Llm As Judge (1)

Top Metrics

  • Accuracy (2)
  • Helpfulness (1)

Top Benchmarks

Quality Controls

  • Calibration (1)

Papers In This Archive Slice

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