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HFEPX Benchmark Hub

WebArena In CS.CL Papers

Updated from current HFEPX corpus (Apr 17, 2026). 8 papers are grouped in this benchmark page.

Read Full Context

Updated from current HFEPX corpus (Apr 17, 2026). 8 papers are grouped in this benchmark page. Common evaluation modes: Simulation Env, Human Eval. Common annotation unit: Trajectory. Frequently cited benchmark: WebArena. Common metric signal: success rate. 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: 8 Last published: Mar 22, 2026 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

2

Papers with explicit benchmark + metric + eval mode fields.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

  • 5 papers explicitly name benchmark datasets in the sampled set.
  • 2 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

  • 25% of papers report explicit human-feedback signals, led by critique/edit feedback.
  • simulation environments appears in 62.5% of papers in this hub.
  • WebArena is a recurring benchmark anchor for cross-paper comparisons in this page.
Protocol Notes (Expanded)

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 unspecified rater pools, and annotation is commonly trajectory-level annotation; use this to scope replication staffing.

Benchmark Interpretation

  • WebArena appears in 100% of hub papers (8/8); use this cohort for benchmark-matched comparisons.
  • OSWorld appears in 25% of hub papers (2/8); use this cohort for benchmark-matched comparisons.

Metric Interpretation

  • success rate is reported in 25% of hub papers (2/8); compare with a secondary metric before ranking methods.
  • task success 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
AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling

Mar 22, 2026

 Human Eval, Llm As Judge Demonstrations Precision, Pass@1 Not reported
When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation

Apr 1, 2026

 Simulation Env Critique Edit Not reported Not reported
Go-Browse: Training Web Agents with Structured Exploration

Jun 4, 2025

 Simulation Env Not reported Success rate Not reported
Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

Feb 15, 2026

 Simulation Env Not reported Not reported Not reported
R-WoM: Retrieval-augmented World Model For Computer-use Agents

Oct 13, 2025

 Simulation Env Not reported Not reported Not reported
WebXSkill: Skill Learning for Autonomous Web Agents

Apr 14, 2026

 Not reported Not reported Not reported Not reported
AdaRubric: Task-Adaptive Rubrics for LLM Agent Evaluation

Mar 22, 2026

 Not reported Not reported Not reported Not reported
AI Planning Framework for LLM-Based Web Agents

Mar 13, 2026

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (25% 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 (62.5% vs 35% target).

  • Gap: Papers with known rater population

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

  • Strong: Papers with known annotation unit

    Coverage is strong (37.5% vs 35% target).

Strengths

  • Most papers provide measurable evaluation context (100% benchmarks, 62.5% metrics).
  • Contains both human-eval and LLM-as-judge protocols for head-to-head methodology comparison.
  • Agentic evaluation appears in 62.5% of papers.

Known Gaps

  • Only 0% of papers report quality controls; prioritize calibration/adjudication evidence.
  • Rater population is under-specified (0% coverage).
  • LLM-as-judge appears without enough inter-annotator agreement reporting.

Suggested Next Analyses

  • Compare papers that report both human_eval and llm_as_judge to quantify judge-human agreement drift.
  • Stratify by benchmark (WebArena vs OSWorld) before comparing methods.
  • Track metric sensitivity by reporting both success rate and task success.

Recommended Queries

Judge vs Human AgreementBenchmark Slice: WebArenaMetric Slice: success rateRecent 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

  • Simulation Env (5)
  • Human Eval (1)
  • Llm As Judge (1)

Human Feedback Mix

  • Critique Edit (1)
  • Demonstrations (1)

Top Benchmarks

  • WebArena (8)
  • OSWorld (2)
  • ToolBench (2)
  • Interruptbench (1)

Top Metrics

  • Success rate (2)
  • Task success (2)
  • Accuracy (1)
  • Cost (1)

Top Papers On This Benchmark

Related Benchmark Hubs

WebArena Benchmark Papers WebArena Benchmark Papers (Last 365 Days) GPQA Or WebArena Benchmark Papers AlpacaEval Or WebArena Benchmark Papers WebArena Ecosystem Benchmark Papers In CS.CL MATH-500 Or WebArena Benchmark Papers MATH-500 Or GPQA Benchmark Papers (20) MMLU Or AIME Or AlpacaEval Benchmark Papers (48) MMLU Or AIME Or GPQA Benchmark Papers (42) GSM8K Or MMLU Or AIME Benchmark Papers (57) MMLU Or AIME Or MATH-500 Benchmark Papers (46) MMLU Or AIME Or SWE-bench Benchmark Papers (51) MMLU Or AIME Benchmark Papers (39) MMLU Or AlpacaEval Or GPQA Benchmark Papers (39) GSM8K Or MMLU Or AlpacaEval Benchmark Papers (51) MMLU Or MATH-500 Or AlpacaEval Benchmark Papers (44) MMLU Or SWE-bench Or AlpacaEval Benchmark Papers (45) MMLU Or AlpacaEval Benchmark Papers (32) GSM8K Or MMLU Or GPQA Benchmark Papers (48) MMLU Or MATH-500 Or GPQA Benchmark Papers (39) MMLU Or SWE-bench Or GPQA Benchmark Papers (42) MMLU Or GPQA Benchmark Papers (29) GSM8K Or MMLU Or MATH-500 Benchmark Papers (50) GSM8K Or MMLU Or SWE-bench Benchmark Papers (55)
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