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HFEPX Archive Slice

HFEPX Daily Archive: 2026-03-26

Updated from current HFEPX corpus (Apr 12, 2026). 151 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 151 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Human Eval. Most common rater population: Domain Experts. Common annotation unit: Ranking. Frequent quality control: Calibration. Frequently cited benchmark: GSM8K. 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 Mar 26, 2026.

Papers: 151 Last published: Mar 26, 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 151 papers).

High-Signal Coverage

100.0%

60 / 60 papers are not low-signal flagged.

Benchmark Anchors

3.3%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

16.7%

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.

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Why This Time Slice Matters

  • 4% of papers report explicit human-feedback signals, led by expert verification.
  • automatic metrics appears in 20.5% of papers in this hub.
  • GSM8K 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 (1.3% of papers).
  • Rater context is mostly domain experts, and annotation is commonly ranking annotation; use this to scope replication staffing.
  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.

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
RenoBench: A Citation Parsing Benchmark

Mar 26, 2026

Automatic Metrics Renobench Precision, Recall Not reported
S2D2: Fast Decoding for Diffusion LLMs via Training-Free Self-Speculation

Mar 26, 2026

Automatic Metrics Not reported Accuracy, Cost Not reported
Measuring What Matters -- or What's Convenient?: Robustness of LLM-Based Scoring Systems to Construct-Irrelevant Factors

Mar 26, 2026

Human Eval Not reported Relevance Not reported
Voxtral TTS

Mar 26, 2026

Human Eval, Automatic Metrics Not reported Win rate Not reported
Humans vs Vision-Language Models: A Unified Measure of Narrative Coherence

Mar 26, 2026

Automatic Metrics Not reported Coherence Not reported
Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties

Mar 26, 2026

Human Eval, Automatic Metrics Not reported Bleu Not reported
Navigating the Prompt Space: Improving LLM Classification of Social Science Texts Through Prompt Engineering

Mar 26, 2026

Automatic Metrics Not reported Accuracy Not reported
GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs

Mar 26, 2026

Automatic Metrics Not reported Accuracy, Precision Not reported
Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics

Mar 26, 2026

Simulation Env Not reported Success rate Not reported
Image Rotation Angle Estimation: Comparing Circular-Aware Methods

Mar 26, 2026

Automatic Metrics Not reported Accuracy, Mae Not reported
Researcher Workflow (Detailed)

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (4% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (2% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (10.6% vs 35% target).

  • Moderate: Papers naming evaluation metrics

    Coverage is usable but incomplete (27.8% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (6% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (6.6% vs 35% target).

Strengths

  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.

Known Gaps

  • Only 2% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (6% coverage).
  • Annotation unit is under-specified (6.6% coverage).

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Stratify by benchmark (GSM8K vs DROP) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.
  • Add inter-annotator agreement checks when reproducing these protocols.

Recommended Queries

Known Limitations
  • Only 2% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (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 (31)
  • Human Eval (5)
  • Simulation Env (3)
  • Llm As Judge (1)

Top Metrics

  • Accuracy (21)
  • Cost (11)
  • F1 (4)
  • Coherence (3)

Top Benchmarks

  • GSM8K (3)
  • DROP (2)
  • MMLU (2)
  • BIRD (1)

Quality Controls

  • Calibration (2)
  • Gold Questions (1)

Papers In This Archive Slice

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