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HFEPX Archive Slice

HFEPX Weekly Archive: 2025-W51

Updated from current HFEPX corpus (Apr 17, 2026). 44 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 17, 2026). 44 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Llm As Judge. Most common rater population: Domain Experts. Common annotation unit: Multi Dim Rubric. Frequent quality control: Calibration. Frequently cited benchmark: BrowseComp. 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 Dec 21, 2025.

Papers: 44 Last published: Dec 21, 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%

44 / 44 papers are not low-signal flagged.

Benchmark Anchors

9.1%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

27.3%

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

  • 9.1% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 25% of papers in this hub.
  • BrowseComp 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 (2.3% of papers).
  • Rater context is mostly domain experts, and annotation is commonly multi-dimensional rubrics; 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
Towards Efficient Agents: A Co-Design of Inference Architecture and System

Dec 20, 2025

Automatic Metrics BrowseComp Accuracy, Latency Not reported
Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning

Dec 18, 2025

Automatic Metrics Not reported Exact match Not reported
Refusal Steering: Fine-grained Control over LLM Refusal Behaviour for Sensitive Topics

Dec 18, 2025

Llm As Judge Jailbreakbench Not reported Not reported
Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills

Dec 18, 2025

Automatic Metrics Not reported Cost Not reported
Knowledge Distillation with Structured Chain-of-Thought for Text-to-SQL

Dec 18, 2025

Automatic Metrics Not reported Cost Not reported
In-Context Algebra

Dec 18, 2025

Automatic Metrics Not reported Accuracy Not reported
TTP: Test-Time Padding for Adversarial Detection and Robust Adaptation on Vision-Language Models

Dec 18, 2025

Automatic Metrics Not reported Accuracy Not reported
A Domain-Adapted Pipeline for Structured Information Extraction from Police Incident Announcements on Social Media

Dec 18, 2025

Automatic Metrics Not reported Accuracy, Exact match Not reported
Imitation Game: Reproducing Deep Learning Bugs Leveraging an Intelligent Agent

Dec 17, 2025

Automatic Metrics Not reported Success rate Not reported
Dual-objective Language Models: Training Efficiency Without Overfitting

Dec 16, 2025

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (9.1% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (2.3% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (11.4% vs 35% target).

  • Moderate: Papers naming evaluation metrics

    Coverage is usable but incomplete (25% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (4.5% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (6.8% vs 35% target).

Strengths

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

Known Gaps

  • Only 2.3% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (4.5% coverage).
  • Annotation unit is under-specified (6.8% coverage).

Suggested Next Analyses

  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Stratify by benchmark (BrowseComp vs CSyMR-Bench) 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 2.3% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (4.5% 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 (11)
  • Llm As Judge (1)

Top Metrics

  • Accuracy (7)
  • Cost (4)
  • Exact match (1)
  • Latency (1)

Top Benchmarks

  • BrowseComp (1)
  • CSyMR Bench (1)
  • DROP (1)
  • IFEval (1)

Quality Controls

  • Calibration (1)

Papers In This Archive Slice

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