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HFEPX Hub

Web Browsing + General (Last 60 Days)

Updated from current HFEPX corpus (Apr 17, 2026). 20 papers are grouped in this hub page.

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Updated from current HFEPX corpus (Apr 17, 2026). 20 papers are grouped in this hub page. Common evaluation modes: Automatic Metrics, Simulation Env. Most common rater population: Domain Experts. Common annotation unit: Trajectory. Frequently cited benchmark: BIRD. 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 Mar 22, 2026.

Papers: 20 Last published: Mar 22, 2026 Global RSS Tag RSS
Web BrowsingGeneralLast 60d

Researcher Quick Triage

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

High-Signal Coverage

100.0%

20 / 20 sampled papers are not low-signal flagged.

Replication-Ready Set

4

Benchmark + metric + eval mode explicitly present.

Judge/Human Comparability

1

Papers containing both `human_eval` and `llm_as_judge`.

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

Primary action: Start with the top 2 papers in “Start Here”, then validate assumptions in the protocol matrix.

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Why This Matters For Eval Research

  • 40% of papers report explicit human-feedback signals, led by demonstration data.
  • automatic metrics appears in 65% of papers in this hub.
  • BIRD is a recurring benchmark anchor for cross-paper comparisons in this page.

Protocol Takeaways

  • 1 sampled papers report both human evaluation and LLM-as-judge, supporting direct agreement checks.
  • Quality-control reporting is sparse in this slice; prioritize papers with explicit calibration or adjudication steps.
  • Rater context is mostly domain experts, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.

Benchmark Interpretation

  • BIRD appears in 5% of hub papers (1/20); use this cohort for benchmark-matched comparisons.
  • Mapg-Bench appears in 5% of hub papers (1/20); use this cohort for benchmark-matched comparisons.

Metric Interpretation

  • accuracy is reported in 40% of hub papers (8/20); compare with a secondary metric before ranking methods.
  • precision is reported in 15% of hub papers (3/20); compare with a secondary metric before ranking methods.
Researcher Checklist (Expanded)

Researcher Checklist

  • Moderate: Papers with explicit human feedback

    Coverage is usable but incomplete (40% vs 45% target).

  • Gap: Papers reporting quality controls

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

  • Moderate: Papers naming benchmarks/datasets

    Coverage is usable but incomplete (25% vs 35% target).

  • Strong: Papers naming evaluation metrics

    Coverage is strong (70% vs 35% target).

  • Gap: Papers with known rater population

    Coverage is a replication risk (5% vs 35% target).

  • Gap: Papers with known annotation unit

    Coverage is a replication risk (20% vs 35% target).

Strengths

  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.
  • Agentic evaluation appears in 100% of papers.

Known Gaps

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (5% coverage).
  • Annotation unit is under-specified (20% coverage).

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Stratify by benchmark (BIRD vs Mapg-Bench) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and precision.
Recommended Queries (Expanded)

Recommended Queries

Start with These 3

Use these when you need one protocol anchor, one benchmark anchor, and one recent comparison point before reading the wider hub.

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
AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling

Mar 22, 2026

Yes Human Eval , Llm As Judge WebArena , ToolBench Precision , Pass@1 Not Reported
SODIUM: From Open Web Data to Queryable Databases

Mar 19, 2026

Yes Automatic Metrics Sodium Bench Accuracy Not Reported
MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks

Feb 18, 2026

Yes Automatic Metrics Memoryarena Recall Not Reported
Meanings and Measurements: Multi-Agent Probabilistic Grounding for Vision-Language Navigation

Mar 19, 2026

Yes Simulation Env Mapg Bench Not Reported Not Reported
BEACON: Language-Conditioned Navigation Affordance Prediction under Occlusion

Mar 10, 2026

No
Not Reported
Automatic Metrics , Simulation Env BIRD Accuracy Not Reported
MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models

Mar 3, 2026

Yes Automatic Metrics Not Reported Success rate , Jailbreak success rate Not Reported
Modeling Distinct Human Interaction in Web Agents

Feb 19, 2026

Yes Automatic Metrics Not Reported Accuracy Not Reported
Aligning Large Language Models with Searcher Preferences

Mar 11, 2026

Yes Not Reported Not Reported Not Reported Not Reported
TimeWarp: Evaluating Web Agents by Revisiting the Past

Mar 5, 2026

Yes Not Reported Not Reported Not Reported Not Reported
Mind over Space: Can Multimodal Large Language Models Mentally Navigate?

Mar 23, 2026

No
Not Reported
Automatic Metrics , Simulation Env Not Reported Accuracy Not Reported
Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics

Mar 26, 2026

No
Not Reported
Simulation Env Not Reported Success rate Not Reported
Rethinking SAR ATR: A Target-Aware Frequency-Spatial Enhancement Framework with Noise-Resilient Knowledge Guidance

Mar 23, 2026

No
Not Reported
Automatic Metrics Not Reported Accuracy , Precision Not Reported

Protocol Diff (Top Papers)

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

Signal AgentHER: Hindsight Experience Replay for LLM Agent… SODIUM: From Open Web Data to Queryable Databases MemoryArena: Benchmarking Agent Memory in Interdepe…
Human Feedback DemonstrationsExpert VerificationPairwise Preference
Evaluation Modes Human Eval, Llm As JudgeAutomatic MetricsAutomatic Metrics
Benchmarks WebArena, ToolBenchSodium BenchMemoryarena
Metrics Precision, Pass@1AccuracyRecall
Quality Controls Not reportedNot reportedNot reported
Rater Population UnknownDomain ExpertsUnknown
Annotation Unit TrajectoryUnknownUnknown
Suggested Reading Order (Extended)

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

Suggested Reading Order

  1. Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics

    Start here for detailed protocol reporting and quality-control evidence. Signals: simulation environments. Focus: success rate. Abstract: Autonomous object search is challenging for mobile robots operating in indoor environments.

  2. Mind over Space: Can Multimodal Large Language Models Mentally Navigate?

    Start here for detailed protocol reporting and quality-control evidence. Signals: automatic metrics. Focus: accuracy. Abstract: Despite the widespread adoption of MLLMs in embodied agents, their capabilities remain largely.

  3. Rethinking SAR ATR: A Target-Aware Frequency-Spatial Enhancement Framework with Noise-Resilient Knowledge Guidance

    Start here for detailed protocol reporting and quality-control evidence. Signals: automatic metrics. Focus: accuracy. Abstract: Synthetic aperture radar automatic target recognition (SAR ATR) is of considerable importance in.

  4. AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling

    Include a human-eval paper to calibrate against judge-based evaluation settings. Signals: human evaluation + demonstration data. Focus: WebArena / precision. Abstract: AgentHER realises this idea through a four-stage.

  5. Meanings and Measurements: Multi-Agent Probabilistic Grounding for Vision-Language Navigation

    Include a human-eval paper to calibrate against judge-based evaluation settings. Signals: simulation environments + demonstration data. Focus: Mapg-Bench. Abstract: Robots collaborating with humans must convert natural language goals.

  6. SODIUM: From Open Web Data to Queryable Databases

    Adds automatic metrics with expert verification for broader protocol coverage within this hub. Signals: automatic metrics + expert verification. Focus: Sodium-Bench / accuracy. Abstract: During research, domain experts.

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

    Adds automatic metrics with pairwise preferences for broader protocol coverage within this hub. Signals: automatic metrics + pairwise preferences. Focus: Memoryarena / recall. Abstract: MemoryArena supports evaluation across.

  8. BEACON: Language-Conditioned Navigation Affordance Prediction under Occlusion

    Adds automatic metrics for broader protocol coverage within this hub. Signals: automatic metrics. Focus: BIRD / accuracy. Abstract: Language-conditioned local navigation requires a robot to infer a nearby.

Known Limitations

Known Limitations

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (5% 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

  • Demonstrations (3)
  • Pairwise Preference (3)
  • Expert Verification (1)
  • Red Team (1)

Evaluation Modes

  • Automatic Metrics (13)
  • Simulation Env (7)
  • Human Eval (1)
  • Llm As Judge (1)

Top Benchmarks

  • BIRD (1)
  • Mapg Bench (1)
  • Memoryarena (1)
  • Sodium Bench (1)

Top Metrics

  • Accuracy (8)
  • Precision (3)
  • Cost (2)
  • Success rate (2)

Rater Population Mix

  • Domain Experts (1)

Quality Controls

Coverage diagnostics (sample-based): human-feedback 40.0% · benchmarks 25.0% · metrics 70.0% · quality controls 0.0%.

Top Papers

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