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HFEPX Metric Hub

Throughput In CS.LG Papers

Updated from current HFEPX corpus (Apr 9, 2026). 17 papers are grouped in this metric page.

Read Full Context

Updated from current HFEPX corpus (Apr 9, 2026). 17 papers are grouped in this metric page. Common evaluation modes: Automatic Metrics, Llm As Judge. Frequently cited benchmark: HumanoidBench. Common metric signal: throughput. 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 7, 2026.

Papers: 17 Last published: Apr 7, 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

17.6%

3 sampled papers include metric names.

Benchmark Anchoring

5.9%

Papers with explicit dataset/benchmark anchors for fair comparison.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

  • 17 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

  • automatic metrics appears in 17.6% of papers in this hub.
  • HumanoidBench is a recurring benchmark anchor for cross-paper comparisons in this page.
  • long-horizon tasks appears in 5.9% of papers, indicating agentic evaluation demand.
Metric Notes (Expanded)

Metric-Driven Protocol Takeaways

  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.
  • Stratify by benchmark (HumanoidBench vs SQuAD) before comparing methods.

Metric Interpretation

  • throughput is reported in 100% of hub papers (17/17); compare with a secondary metric before ranking methods.
  • cost is reported in 47.1% of hub papers (8/17); compare with a secondary metric before ranking methods.

Benchmark Context

  • HumanoidBench appears in 5.9% of hub papers (1/17); use this cohort for benchmark-matched comparisons.
  • SQuAD appears in 5.9% of hub papers (1/17); 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
Weakly Supervised Distillation of Hallucination Signals into Transformer Representations

Apr 7, 2026

 F1, Latency SQuAD Llm As Judge, Automatic Metrics Not reported
Learning When to Attend: Conditional Memory Access for Long-Context LLMs

Mar 18, 2026

 Throughput, Context length 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
FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control

Apr 6, 2026

 Not reported Not reported Not reported Not reported
Sparser, Faster, Lighter Transformer Language Models

Mar 24, 2026

 Not reported Not reported Not reported Not reported
Benchmarking Multi-Agent LLM Architectures for Financial Document Processing: A Comparative Study of Orchestration Patterns, Cost-Accuracy Tradeoffs and Production Scaling Strategies

Mar 24, 2026

 Not reported Not reported Not reported Not reported
MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning

Mar 21, 2026

 Not reported Not reported Not reported Not reported
Cost-Efficient Multimodal LLM Inference via Cross-Tier GPU Heterogeneity

Mar 13, 2026

 Not reported Not reported Not reported Not reported
FastDSAC: Unlocking the Potential of Maximum Entropy RL in High-Dimensional Humanoid Control

Mar 13, 2026

 Not reported Not reported Not reported Not reported
Proof-Carrying Materials: Falsifiable Safety Certificates for Machine-Learned Interatomic Potentials

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 (0% 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 (11.8% 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 (0% 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 (0% coverage).

Suggested Next Analyses

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

Recommended Queries

LLM-as-Judge ProtocolsBenchmark Slice: HumanoidBenchMetric Slice: throughputRecent 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

  • Throughput (17)
  • Cost (8)
  • Latency (7)
  • Accuracy (5)

Evaluation Modes

  • Automatic Metrics (3)
  • Llm As Judge (2)

Top Benchmarks

  • HumanoidBench (1)
  • SQuAD (1)

Agentic Mix

  • Long Horizon (1)

Top Papers Reporting This Metric

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