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HFEPX Benchmark Hub

HumanEval+ In CS.AI Papers

Updated from current HFEPX corpus (Apr 27, 2026). 8 papers are grouped in this benchmark page.

Read Full Context

Updated from current HFEPX corpus (Apr 27, 2026). 8 papers are grouped in this benchmark page. Common evaluation modes: Automatic Metrics. Frequently cited benchmark: HumanEval+. 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 Nov 17, 2025.

Papers: 8 Last published: Nov 17, 2025 Global RSS

Researcher Quick Triage

Use this page for benchmark-matched method comparisons and eval protocol selection. Quality band: Developing .

High-Signal Coverage

100.0%

8 / 8 sampled papers are not low-signal flagged.

Replication-Ready Set

1

Papers with explicit benchmark + metric + eval mode fields.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

  • 1 papers explicitly name benchmark datasets in the sampled set.
  • 1 papers report at least one metric term in metadata extraction.
  • Start with the ranked shortlist below before reading all papers.

Primary action: Use this page to map benchmark mentions first; wait for stronger metric/QC coverage before strict comparisons.

Why This Matters (Expanded)

Why This Matters For Eval Research

  • automatic metrics appears in 12.5% of papers in this hub.
  • HumanEval+ is a recurring benchmark anchor for cross-paper comparisons in this page.
  • multi-agent setups appears in 12.5% of papers, indicating agentic evaluation demand.
Protocol Notes (Expanded)

Protocol Takeaways

  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Stratify by benchmark (HumanEval+ vs GSM8K) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.

Benchmark Interpretation

  • HumanEval+ appears in 100% of hub papers (8/8); use this cohort for benchmark-matched comparisons.
  • GSM8K appears in 37.5% of hub papers (3/8); use this cohort for benchmark-matched comparisons.

Metric Interpretation

  • accuracy is reported in 37.5% of hub papers (3/8); compare with a secondary metric before ranking methods.
  • cost is reported in 25% of hub papers (2/8); compare with a secondary metric before ranking methods.

Start Here (Benchmark-Matched First 6)

Ranked by protocol completeness so you can quickly find papers suitable for comparison studies.

Protocol Matrix (Top 10)

Compare protocol ingredients quickly before deep-reading full papers.

Paper Eval Modes Human Feedback Metrics Quality Controls
Cost-Effective Communication: An Auction-based Method for Language Agent Interaction

Nov 17, 2025

 Automatic Metrics Not reported Pass@1, Cost Not reported
RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding

Apr 16, 2026

 Not reported Not reported Not reported Not reported
StoryCoder: Narrative Reformulation for Structured Reasoning in LLM Code Generation

Apr 16, 2026

 Not reported Not reported Not reported Not reported
Sensitivity-Positional Co-Localization in GQA Transformers

Apr 9, 2026

 Not reported Not reported Not reported Not reported
TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning

Mar 13, 2026

 Not reported Not reported Not reported Not reported
In-Context Environments Induce Evaluation-Awareness in Language Models

Mar 4, 2026

 Not reported Not reported Not reported Not reported
Bridging Draft Policy Misalignment: Group Tree Optimization for Speculative Decoding

Sep 26, 2025

 Not reported Not reported Not reported Not reported
SafeSieve: From Heuristics to Experience in Progressive Pruning for LLM-based Multi-Agent Communication

Aug 15, 2025

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (0% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (0% vs 30% target).

  • Strong: Papers naming benchmarks/datasets

    Coverage is strong (100% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (75% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (0% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (0% vs 35% target).

Strengths

  • Most papers provide measurable evaluation context (100% benchmarks, 75% metrics).

Known Gaps

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (0% coverage).
  • Annotation unit is under-specified (0% coverage).

Suggested Next Analyses

  • Stratify by benchmark (HumanEval+ vs GSM8K) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and cost.

Recommended Queries

Benchmark Slice: HumanEval+Metric Slice: accuracyRecent High-Signal Papers
Known Limitations
  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (0% 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 (1)

Human Feedback Mix

Top Benchmarks

  • HumanEval+ (8)
  • GSM8K (3)
  • MMLU (3)
  • GPQA (2)

Top Metrics

  • Accuracy (3)
  • Cost (2)
  • Coherence (1)
  • Exact match (1)

Top Papers On This Benchmark

Related Benchmark Hubs

HumanEval+ Benchmark Papers (Last 300 Days) HumanEval+ Benchmark Papers (Last 365 Days) HumanEval+ Benchmark Papers HumanEval+ Or BFCL Benchmark Papers HumanEval+ Or LongBench Benchmark Papers HumanEval+ Or WebArena Benchmark Papers GPQA Or BFCL Benchmark Papers (23) HumanEval+ Or BFCL Benchmark Papers (21) MATH-500 Or BFCL Benchmark Papers (25) GPQA Or HumanEval+ Benchmark Papers (22) MATH-500 Or GPQA Benchmark Papers (25) MATH-500 Or HumanEval+ Benchmark Papers (24) MATH-500 Benchmark Papers (15) MMLU Or AIME Or AlpacaEval Benchmark Papers (60) MMLU Or AIME Or BFCL Benchmark Papers (59) GSM8K Or MMLU Or AIME Benchmark Papers (72) MMLU Or AIME Or HotpotQA Benchmark Papers (62) MMLU Or AIME Or HumanEval+ Benchmark Papers (57) MMLU Or AIME Or LiveCodeBench Benchmark Papers (59) MMLU Or AIME Or LongBench Benchmark Papers (59) MMLU Or AIME Or MATH-500 Benchmark Papers (58) MMLU Or AIME Or SWE-bench Benchmark Papers (64) MMLU Or AIME Benchmark Papers (50) GSM8K Or MMLU Or AlpacaEval Benchmark Papers (65)
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