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HFEPX Archive Slice

HFEPX Daily Archive: 2026-02-11

Updated from current HFEPX corpus (Apr 12, 2026). 19 papers are grouped in this daily page.

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Updated from current HFEPX corpus (Apr 12, 2026). 19 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Pairwise. Frequent quality control: Calibration. Frequently cited benchmark: agent-diff-bench. 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 Feb 11, 2026.

Papers: 19 Last published: Feb 11, 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: Medium .

High-Signal Coverage

100.0%

19 / 19 papers are not low-signal flagged.

Benchmark Anchors

21.1%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

26.3%

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 as early signal only; benchmark/metric anchoring is limited for rigorous period-over-period claims.

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Why This Time Slice Matters

  • 10.5% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 10.5% of papers in this hub.
  • agent-diff-bench 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 (5.3% of papers).
  • Rater context is mostly domain experts, and annotation is commonly pairwise annotation; use this to scope replication staffing.
  • Stratify by benchmark (agent-diff-bench vs BrowseComp) before comparing methods.

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
Agent-Diff: Benchmarking LLM Agents on Enterprise API Tasks via Code Execution with State-Diff-Based Evaluation

Feb 11, 2026

Automatic Metrics Agent Diff Bench Task success Not reported
Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters

Feb 11, 2026

Not reported LiveCodeBench, BrowseComp Latency, Cost Not reported
Advancing AI Trustworthiness Through Patient Simulation: Risk Assessment of Conversational Agents for Antidepressant Selection

Feb 11, 2026

Simulation Env Not reported Kappa, Agreement Inter Annotator Agreement Reported
The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Task

Feb 11, 2026

Automatic Metrics Not reported Accuracy Not reported
Voxtral Realtime

Feb 11, 2026

Not reported Not reported Latency Not reported
DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning

Feb 11, 2026

Not reported AIME Not reported Not reported
Search or Accelerate: Confidence-Switched Position Beam Search for Diffusion Language Models

Feb 11, 2026

Not reported GSM8K, HumanEval+ Not reported Not reported
Learning Page Order in Shuffled WOO Releases

Feb 11, 2026

Not reported Not reported Not reported Not reported
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation

Feb 11, 2026

Not reported Not reported Not reported Calibration
When Models Examine Themselves: Vocabulary-Activation Correspondence in Self-Referential Processing

Feb 11, 2026

Not reported Not reported Not reported Not reported
Researcher Workflow (Detailed)

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (10.5% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (10.5% vs 30% target).

  • Moderate: Papers naming benchmarks/datasets

    Coverage is usable but incomplete (21.1% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (36.8% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (15.8% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (5.3% vs 35% target).

Strengths

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

Known Gaps

  • Only 10.5% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (15.8% coverage).
  • Annotation unit is under-specified (5.3% coverage).

Suggested Next Analyses

  • Stratify by benchmark (agent-diff-bench vs BrowseComp) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.

Recommended Queries

Known Limitations
  • Only 10.5% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (15.8% 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 (2)
  • Simulation Env (1)

Top Metrics

  • Accuracy (4)
  • Cost (1)
  • Latency (1)
  • Relevance (1)

Top Benchmarks

  • Agent Diff Bench (1)
  • BrowseComp (1)
  • GraphBench (1)
  • Imo Answerbench (1)

Quality Controls

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

Papers In This Archive Slice

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