Skip to content
← Back to explorer

HFEPX Metric Hub

Inference Cost In CS.LG Papers

Updated from current HFEPX corpus (Apr 9, 2026). 11 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Apr 9, 2026). 11 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Llm As Judge. Common annotation unit: Multi Dim Rubric. Frequently cited benchmark: GSM8K. Common metric signal: cost. 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 Apr 6, 2026.

Papers: 11 Last published: Apr 6, 2026 Global RSS

Researcher Quick Triage

Use this page to compare metric behavior across protocols and benchmarks before selecting your reporting stack. Quality band: Developing .

Metric Coverage

27.3%

3 sampled papers include metric names.

Benchmark Anchoring

9.1%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

  • 11 papers are not low-signal flagged in this sample.
  • Use the protocol matrix below to avoid comparing metrics across incompatible eval setups.

Primary action: Treat this as directional signal only; metric reporting is present but benchmark anchoring is still thin.

Why This Matters (Expanded)

Why This Matters For Eval Research

  • 9.1% of papers report explicit human-feedback signals, led by rubric ratings.
  • automatic metrics appears in 27.3% of papers in this hub.
  • GSM8K is a recurring benchmark anchor for cross-paper comparisons in this page.
Metric Notes (Expanded)

Metric-Driven Protocol Takeaways

  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Rater context is mostly unspecified rater pools, 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.

Metric Interpretation

  • cost is reported in 100% of hub papers (11/11); compare with a secondary metric before ranking methods.
  • inference cost is reported in 100% of hub papers (11/11); compare with a secondary metric before ranking methods.

Benchmark Context

  • GSM8K appears in 9.1% of hub papers (1/11); use this cohort for benchmark-matched comparisons.
  • HumanEval+ appears in 9.1% of hub papers (1/11); use this cohort for benchmark-matched comparisons.

Start Here (Metric-Reliable First 6)

Ranked for metric reporting completeness and comparability.

Metric Protocol Matrix (Top 10)

Compare metric, benchmark, and evaluation context side by side.

Paper Metrics Benchmarks Eval Modes Quality Controls
S0 Tuning: Zero-Overhead Adaptation of Hybrid Recurrent-Attention Models

Apr 1, 2026

 Pass@1, Cost MATH 500, GSM8K Automatic Metrics Not reported
QED-Nano: Teaching a Tiny Model to Prove Hard Theorems

Apr 6, 2026

 Cost, Inference cost Not reported Automatic Metrics Not reported
Luna-2: Scalable Single-Token Evaluation with Small Language Models

Feb 20, 2026

 Accuracy, Latency Not reported Llm As Judge, Automatic Metrics Not reported
Are Latent Reasoning Models Easily Interpretable?

Apr 6, 2026

 Not reported Not reported Not reported Not reported
GAIN: Multiplicative Modulation for Domain Adaptation

Apr 6, 2026

 Not reported Not reported Not reported Not reported
VISion On Request: Enhanced VLLM efficiency with sparse, dynamically selected, vision-language interactions

Mar 24, 2026

 Not reported Not reported Not reported Not reported
Auto-Unrolled Proximal Gradient Descent: An AutoML Approach to Interpretable Waveform Optimization

Mar 18, 2026

 Not reported Not reported Not reported Not reported
Ensemble Self-Training for Unsupervised Machine Translation

Mar 17, 2026

 Not reported Not reported Not reported Not reported
Thinking in Latents: Adaptive Anchor Refinement for Implicit Reasoning in LLMs

Mar 16, 2026

 Not reported Not reported Not reported Not reported
Slow-Fast Inference: Training-Free Inference Acceleration via Within-Sentence Support Stability

Mar 12, 2026

 Not reported Not reported Not reported 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 (0% vs 30% target).

  • Gap: Papers naming benchmarks/datasets

    Coverage is a replication risk (9.1% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (100% 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 (18.2% vs 35% target).

Strengths

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

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 (18.2% coverage).

Suggested Next Analyses

  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Stratify by benchmark (GSM8K vs HumanEval+) before comparing methods.
  • Track metric sensitivity by reporting both cost and inference cost.

Recommended Queries

LLM-as-Judge ProtocolsBenchmark Slice: GSM8KMetric Slice: costRecent 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)

Top Metrics

  • Cost (11)
  • Inference cost (11)
  • Accuracy (3)
  • Throughput (2)

Evaluation Modes

  • Automatic Metrics (3)
  • Llm As Judge (1)

Top Benchmarks

  • GSM8K (1)
  • HumanEval+ (1)
  • MATH 500 (1)
  • Spider (1)

Agentic Mix

  • Long Horizon (1)

Top Papers Reporting This Metric

Related Metric Hubs

Inference Cost Metric Papers CS.LG Human Feedback And Eval Papers Inference Cost In CS.AI Papers CS.LG Papers (Last 60 Days) CS.LG Papers (Last 90 Days) CS.LG Papers (Last 30 Days) Helpfulness In CS.CL Papers (12) Helpfulness Metric Papers (15) Relevance + Automatic Metrics Metric Papers (Last 120 Days) (18) Relevance + Automatic Metrics Metric Papers (Last 30 Days) (10) Relevance + Automatic Metrics Metric Papers (Last 45 Days) (14) Relevance + Automatic Metrics Metric Papers (Last 60 Days) (16) Relevance + Automatic Metrics Metric Papers (Last 90 Days) (17) Relevance + Automatic Metrics Metric Papers (22) Relevance + General Metric Papers (Last 120 Days) (11) Relevance + General Metric Papers (Last 45 Days) (10) Relevance + General Metric Papers (Last 60 Days) (11) Relevance + General Metric Papers (Last 90 Days) (11) Relevance + General Metric Papers (12) Relevance + Pairwise Preference Metric Papers (Last 120 Days) (10) Relevance + Pairwise Preference Metric Papers (11) Relevance In CS.CL Papers (40) Relevance In CS.LG Papers (13) Relevance Metric Papers (65)

Need human evaluators for your AI research? Scale annotation with expert AI Trainers.

Post a Job Get a Quote