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HFEPX Archive Slice

HFEPX Daily Archive: 2026-02-16

Updated from current HFEPX corpus (Apr 12, 2026). 63 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 63 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Llm As Judge. Most common rater population: Domain Experts. Common annotation unit: Freeform. Frequent quality control: Calibration. Frequently cited benchmark: Innoeval. Common metric signal: bleu. 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 16, 2026.

Papers: 63 Last published: Feb 16, 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 63 papers).

High-Signal Coverage

100.0%

60 / 60 papers are not low-signal flagged.

Benchmark Anchors

13.3%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

45.0%

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

  • 11.1% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 31.7% of papers in this hub.
  • Innoeval 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 (3.2% of papers).
  • Rater context is mostly domain experts, and annotation is commonly Freeform; 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
Scaling Beyond Masked Diffusion Language Models

Feb 16, 2026

Automatic Metrics GSM8K Perplexity Not reported
LLMStructBench: Benchmarking Large Language Model Structured Data Extraction

Feb 16, 2026

Automatic Metrics Llmstructbench Accuracy Not reported
Evolutionary System Prompt Learning for Reinforcement Learning in LLMs

Feb 16, 2026

Automatic Metrics AIME Success rate Not reported
HyperRAG: Reasoning N-ary Facts over Hypergraphs for Retrieval Augmented Generation

Feb 16, 2026

Automatic Metrics HotpotQA Accuracy, Mrr Not reported
Robust Bias Evaluation with FilBBQ: A Filipino Bias Benchmark for Question-Answering Language Models

Feb 16, 2026

Automatic Metrics BBQ Accuracy Not reported
Counterfactual Fairness Evaluation of LLM-Based Contact Center Agent Quality Assurance System

Feb 16, 2026

Automatic Metrics Not reported Accuracy Calibration
Feature Recalibration Based Olfactory-Visual Multimodal Model for Enhanced Rice Deterioration Detection

Feb 16, 2026

Automatic Metrics Not reported Accuracy Calibration
TruthStance: An Annotated Dataset of Conversations on Truth Social

Feb 16, 2026

Automatic Metrics Not reported Agreement Inter Annotator Agreement Reported
Weight space Detection of Backdoors in LoRA Adapters

Feb 16, 2026

Automatic Metrics Not reported Accuracy Not reported
Seeing to Generalize: How Visual Data Corrects Binding Shortcuts

Feb 16, 2026

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (11.1% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (6.3% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (1.6% vs 35% target).

  • Gap: Papers naming evaluation metrics

    Coverage is a replication risk (3.2% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (12.7% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (6.3% vs 35% target).

Strengths

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

Known Gaps

  • Only 6.3% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (12.7% coverage).
  • Annotation unit is under-specified (6.3% coverage).

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Track metric sensitivity by reporting both bleu and f1.

Recommended Queries

Known Limitations
  • Only 6.3% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (12.7% 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 (20)
  • Llm As Judge (2)
  • Human Eval (1)

Top Metrics

  • Bleu (1)
  • F1 (1)
  • Rouge (1)

Top Benchmarks

  • Innoeval (1)

Quality Controls

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

Papers In This Archive Slice

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