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HFEPX Hub

Web Browsing + General (Last 30 Days)

Updated from current HFEPX corpus (Mar 1, 2026). 11 papers are grouped in this hub page.

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Updated from current HFEPX corpus (Mar 1, 2026). 11 papers are grouped in this hub page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Trajectory. Frequent quality control: Adjudication. 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 Feb 18, 2026.

Papers: 11 Last published: Feb 18, 2026 Global RSS Tag RSS
Web BrowsingGeneralLast 30d

Researcher Quick Triage

This hub is best used for protocol triage and replication planning from abstract-level evidence. Quality band: Developing .

All Sampled Papers (11) Replication-Ready Only (1)

High-Signal Coverage

100.0%

11 / 11 sampled papers are not low-signal flagged.

Replication-Ready Set

1

Benchmark + metric + eval mode explicitly present.

Judge/Human Comparability

0

Papers containing both `human_eval` and `llm_as_judge`.

  • 1 papers are replication-ready (benchmark + metric + explicit evaluation mode).
  • 0 papers support judge-vs-human agreement analysis.
  • 1 papers report explicit quality controls (calibration/adjudication/IAA).

Primary action: Use this page for scouting only; collect additional papers before attempting replication-critical comparisons.

Why This Matters (Expanded)

Why This Matters For Eval Research

  • 18.2% of papers report explicit human-feedback signals, led by pairwise preferences.
  • automatic metrics appears in 63.6% of papers in this hub.
  • BrowseComp is a recurring benchmark anchor for cross-paper comparisons in this page.
Protocol Notes (Expanded)

Protocol Takeaways

  • Most common quality-control signal is adjudication (9.1% of papers).
  • Rater context is mostly domain experts, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.
  • Pair this hub with a human_eval-heavy hub to validate judge-model calibration.

Benchmark Interpretation

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

Metric Interpretation

  • accuracy is reported in 27.3% of hub papers (3/11); compare with a secondary metric before ranking methods.
  • latency is reported in 9.1% of hub papers (1/11); compare with a secondary metric before ranking methods.
Researcher Checklist (Expanded)

Researcher Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (18.2% vs 45% target).

  • Gap: Papers reporting quality controls

    Coverage is a replication risk (9.1% vs 30% target).

  • Strong: Papers naming benchmarks/datasets

    Coverage is strong (36.4% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (54.5% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (18.2% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (18.2% vs 35% target).

Strengths

  • Most papers provide measurable evaluation context (36.4% benchmarks, 54.5% metrics).
  • Agentic evaluation appears in 100% of papers.

Known Gaps

  • Only 9.1% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (18.2% 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 (BrowseComp vs Innoeval) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and latency.
  • Add inter-annotator agreement checks when reproducing these protocols.
Recommended Queries (Expanded)

Recommended Queries

LLM-as-Judge Protocols Benchmark Slice: BrowseComp Metric Slice: accuracy Recent High-Signal Papers

Start Here (Best First 6)

Ranked for protocol completeness (human signal, benchmark + metric anchors, quality controls, and judge/human overlap).

Protocol Matrix (Top 12)

Use this to quickly compare protocol ingredients instead of scanning long prose.

Paper HF Signal Eval Modes Benchmarks Metrics QC
MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks

Feb 18, 2026

 Yes
Pairwise Preference
Automatic Metrics Memoryarena Recall Not Reported
InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem

Feb 16, 2026

 No
Not Reported
Llm As Judge Innoeval Not Reported Adjudication
Modeling Distinct Human Interaction in Web Agents

Feb 19, 2026

 Yes
Pairwise Preference
Automatic Metrics Not Reported Accuracy Not Reported
Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

Feb 15, 2026

 No
Not Reported
Simulation Env WebArena , OSWorld Not Reported Not Reported
BrowseComp-$V^3$: A Visual, Vertical, and Verifiable Benchmark for Multimodal Browsing Agents

Feb 13, 2026

 No
Not Reported
Automatic Metrics , Simulation Env Not Reported Accuracy Not Reported
Spatio-Temporal Token Pruning for Efficient High-Resolution GUI Agents

Feb 26, 2026

 No
Not Reported
Automatic Metrics Not Reported Precision , Latency Not Reported
Mind the Style: Impact of Communication Style on Human-Chatbot Interaction

Feb 19, 2026

 No
Not Reported
Automatic Metrics Not Reported Task success Not Reported
The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Task

Feb 11, 2026

 No
Not Reported
Automatic Metrics Not Reported Accuracy Not Reported
Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids

Feb 24, 2026

 No
Not Reported
Simulation Env Not Reported Not Reported Not Reported
Contextual Safety Reasoning and Grounding for Open-World Robots

Feb 23, 2026

 No
Not Reported
Simulation Env Not Reported Not Reported Not Reported
Onboard-Targeted Segmentation of Straylight in Space Camera Sensors

Feb 24, 2026

 No
Not Reported
Automatic Metrics Not Reported Not Reported Not Reported

Protocol Diff (Top Papers)

Fast side-by-side comparison for the highest-ranked papers in this hub.

Signal MemoryArena: Benchmarking Agent Memory in Interdepe… InnoEval: On Research Idea Evaluation as a Knowledg… Modeling Distinct Human Interaction in Web Agents
Human Feedback Pairwise PreferenceNot reportedPairwise Preference
Evaluation Modes Automatic MetricsLlm As JudgeAutomatic Metrics
Benchmarks MemoryarenaInnoevalNot reported
Metrics RecallNot reportedAccuracy
Quality Controls Not reportedAdjudicationNot reported
Rater Population UnknownDomain ExpertsUnknown
Annotation Unit UnknownUnknownUnknown
Suggested Reading Order (Extended)

This section is intentionally expanded only when needed; use “Start Here” above for a faster pass.

Suggested Reading Order

  1. Spatio-Temporal Token Pruning for Efficient High-Resolution GUI Agents

    Start here for detailed protocol reporting and quality-control evidence. Signals: automatic metrics. Focus: precision. Abstract: Pure-vision GUI agents provide universal interaction capabilities but suffer from severe efficiency bottlenecks.

  2. Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids

    Start here for detailed protocol reporting and quality-control evidence. Signals: simulation environments. Abstract: Hierarchical, multi-resolution volumetric mapping approaches are widely used to represent large and complex environments as.

  3. Onboard-Targeted Segmentation of Straylight in Space Camera Sensors

    Start here for detailed protocol reporting and quality-control evidence. Signals: automatic metrics. Abstract: This study details an artificial intelligence (AI)-based methodology for the semantic segmentation of space camera.

  4. MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks

    Include a human-eval paper to calibrate against judge-based evaluation settings. Signals: automatic metrics + pairwise preferences. Focus: Memoryarena / recall. Abstract: MemoryArena supports evaluation across web navigation, preference-constrained.

  5. InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem

    Include a human-eval paper to calibrate against judge-based evaluation settings. Signals: LLM-as-judge. Focus: Innoeval. Abstract: However, existing idea evaluation methods often suffer from narrow knowledge horizons, flattened evaluation.

  6. Modeling Distinct Human Interaction in Web Agents

    Adds automatic metrics with pairwise preferences for broader protocol coverage within this hub. Signals: automatic metrics + pairwise preferences. Focus: accuracy. Abstract: Despite rapid progress in autonomous web.

  7. Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

    Adds simulation environments for broader protocol coverage within this hub. Signals: simulation environments. Focus: WebArena. Abstract: The paper introduces GUI-Owl-1.5, the latest native GUI agent model that features.

  8. BrowseComp-$V^3$: A Visual, Vertical, and Verifiable Benchmark for Multimodal Browsing Agents

    Adds automatic metrics for broader protocol coverage within this hub. Signals: automatic metrics. Focus: accuracy. Abstract: Multimodal large language models (MLLMs), equipped with increasingly advanced planning and tool-use.

Known Limitations

Known Limitations

  • Only 9.1% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (18.2% coverage).
  • Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.
Research Utility Snapshot (Detailed)

Research Utility Snapshot

Human Feedback Mix

  • Pairwise Preference (2)

Evaluation Modes

  • Automatic Metrics (7)
  • Simulation Env (4)
  • Llm As Judge (1)

Top Benchmarks

  • BrowseComp (1)
  • Innoeval (1)
  • Memoryarena (1)
  • OSWorld (1)

Top Metrics

  • Accuracy (3)
  • Latency (1)
  • Precision (1)
  • Recall (1)

Rater Population Mix

  • Domain Experts (2)

Quality Controls

  • Adjudication (1)
Coverage diagnostics (sample-based): human-feedback 18.2% · benchmarks 27.3% · metrics 54.5% · quality controls 9.1%.

Top Papers

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