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HFEPX Archive Slice

HFEPX Weekly Archive: 2026-W01

Updated from current HFEPX corpus (Apr 12, 2026). 28 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 28 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Llm As Judge. Most common rater population: Domain Experts. Common annotation unit: Ranking. Frequent quality control: Calibration. Frequently cited benchmark: FCMBench. 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 Jan 4, 2026.

Papers: 28 Last published: Jan 4, 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 .

High-Signal Coverage

100.0%

28 / 28 papers are not low-signal flagged.

Benchmark Anchors

14.3%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

35.7%

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

  • 14.3% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 28.6% of papers in this hub.
  • FCMBench 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 (3.6% of papers).
  • Rater context is mostly domain experts, and annotation is commonly ranking 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
Fast-weight Product Key Memory

Jan 2, 2026

Automatic Metrics Needle In A Haystack Perplexity, Cost Not reported
VL-RouterBench: A Benchmark for Vision-Language Model Routing

Dec 29, 2025

Automatic Metrics Vl Routerbench Accuracy, Throughput Not reported
From Evidence-Based Medicine to Knowledge Graph: Retrieval-Augmented Generation for Sports Rehabilitation and a Domain Benchmark

Jan 1, 2026

Automatic Metrics Not reported Accuracy, Recall Not reported
WISE: Web Information Satire and Fakeness Evaluation

Dec 30, 2025

Automatic Metrics Not reported Accuracy, F1 Calibration
JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese Large Language Models

Jan 4, 2026

Not reported Jmedethicbench Not reported Not reported
Vision-language models lag human performance on physical dynamics and intent reasoning

Jan 4, 2026

Automatic Metrics Not reported Accuracy Not reported
RAIR: A Rule-Aware Benchmark Uniting Challenging Long-Tail and Visual Salience Subset for E-commerce Relevance Assessment

Dec 31, 2025

Automatic Metrics Not reported Relevance Not reported
Paragraph Segmentation Revisited: Towards a Standard Task for Structuring Speech

Dec 30, 2025

Automatic Metrics Not reported Accuracy, Cost Not reported
Multi-Agent LLMs for Generating Research Limitations

Dec 30, 2025

Llm As Judge, Automatic Metrics Not reported Bleu, Rouge Not reported
A Language-Agnostic Hierarchical LoRA-MoE Architecture for CTC-based Multilingual ASR

Jan 2, 2026

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (14.3% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (3.6% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (7.1% vs 35% target).

  • Gap: Papers naming evaluation metrics

    Coverage is a replication risk (14.3% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (10.7% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (14.3% vs 35% target).

Strengths

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

Known Gaps

  • Only 3.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (10.7% coverage).
  • Annotation unit is under-specified (14.3% coverage).

Suggested Next Analyses

  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Stratify by benchmark (FCMBench vs Jmedethicbench) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and bleu.
  • Add inter-annotator agreement checks when reproducing these protocols.

Recommended Queries

Known Limitations
  • Only 3.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (10.7% 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 (8)
  • Llm As Judge (1)

Top Metrics

  • Accuracy (1)
  • Bleu (1)
  • Cost (1)
  • F1 (1)

Top Benchmarks

  • FCMBench (1)
  • Jmedethicbench (1)

Quality Controls

  • Calibration (1)

Papers In This Archive Slice

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