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HFEPX Archive Slice

HFEPX Daily Archive: 2026-03-14

Updated from current HFEPX corpus (Apr 12, 2026). 36 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 36 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Human Eval. Most common rater population: Domain Experts. Common annotation unit: Freeform. Frequent quality control: Gold Questions. Frequently cited benchmark: Deceptarena. 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 14, 2026.

Papers: 36 Last published: Mar 14, 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%

36 / 36 papers are not low-signal flagged.

Benchmark Anchors

22.2%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

44.4%

Papers with reported metric mentions in extraction output.

  • 2 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 expert verification.
  • automatic metrics appears in 44.4% of papers in this hub.
  • Deceptarena is a recurring benchmark anchor for cross-paper comparisons in this page.

Protocol Takeaways For This Period

  • Most common quality-control signal is gold-question checks (5.6% of papers).
  • Rater context is mostly domain experts, and annotation is commonly Freeform; use this to scope replication staffing.
  • Pair this hub with llm_as_judge pages to benchmark automated-vs-human evaluation tradeoffs.

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
SemEval-2026 Task 6: CLARITY -- Unmasking Political Question Evasions

Mar 14, 2026

Automatic Metrics Semeval F1, F1 macro Not reported
QuarkMedBench: A Real-World Scenario Driven Benchmark for Evaluating Large Language Models

Mar 14, 2026

Automatic Metrics Quarkmedbench Accuracy Not reported
The Reasoning Bottleneck in Graph-RAG: Structured Prompting and Context Compression for Multi-Hop QA

Mar 14, 2026

Automatic Metrics HotpotQA Accuracy, Cost Not reported
FLUX: Data Worth Training On

Mar 14, 2026

Automatic Metrics MMLU Accuracy, Cost Not reported
ToolFlood: Beyond Selection -- Hiding Valid Tools from LLM Agents via Semantic Covering

Mar 14, 2026

Automatic Metrics ToolBench Success rate, Jailbreak success rate Not reported
DeceptGuard :A Constitutional Oversight Framework For Detecting Deception in LLM Agents

Mar 14, 2026

Automatic Metrics, Simulation Env Deceptarena Faithfulness Not reported
Knowledge Distillation for Large Language Models

Mar 14, 2026

Automatic Metrics Codeforces Rouge, Latency Not reported
Step-CoT: Stepwise Visual Chain-of-Thought for Medical Visual Question Answering

Mar 14, 2026

Automatic Metrics Not reported Accuracy Not reported
MMOU: A Massive Multi-Task Omni Understanding and Reasoning Benchmark for Long and Complex Real-World Videos

Mar 14, 2026

Automatic Metrics Not reported Accuracy Not reported
CMHL: Contrastive Multi-Head Learning for Emotionally Consistent Text Classification

Mar 14, 2026

Automatic Metrics Not reported F1, Recall 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 (5.6% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (11.1% vs 35% target).

  • Gap: Papers naming evaluation metrics

    Coverage is a replication risk (16.7% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (13.9% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (5.6% vs 35% target).

Strengths

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

Known Gaps

  • Only 5.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (13.9% coverage).
  • Annotation unit is under-specified (5.6% coverage).

Suggested Next Analyses

  • Pair this hub with llm_as_judge pages to benchmark automated-vs-human evaluation tradeoffs.
  • Stratify by benchmark (Deceptarena vs Quarkmedbench) 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 5.6% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (13.9% 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 (16)
  • Human Eval (1)
  • Simulation Env (1)

Top Metrics

  • Accuracy (3)
  • Cost (1)
  • F1 (1)
  • F1 macro (1)

Top Benchmarks

  • Deceptarena (1)
  • Quarkmedbench (1)
  • Semeval (1)
  • ToolBench (1)

Quality Controls

  • Gold Questions (2)

Papers In This Archive Slice

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