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HFEPX Benchmark Hub

BFCL Or WebArena Benchmark Papers

Updated from current HFEPX corpus (Apr 27, 2026). 20 papers are grouped in this benchmark page.

Read Full Context

Updated from current HFEPX corpus (Apr 27, 2026). 20 papers are grouped in this benchmark page. Common evaluation modes: Simulation Env, Automatic Metrics. Common annotation unit: Trajectory. Frequently cited benchmark: WebArena. 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

Researcher Quick Triage

Use this page for benchmark-matched method comparisons and eval protocol selection. Quality band: Medium .

High-Signal Coverage

100.0%

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

Replication-Ready Set

6

Papers with explicit benchmark + metric + eval mode fields.

Quality Controls

0.0%

0 papers report calibration/adjudication/IAA controls.

  • 9 papers explicitly name benchmark datasets in the sampled set.
  • 6 papers report at least one metric term in metadata extraction.
  • Start with the ranked shortlist below before reading all papers.

Primary action: Start with the top 2 benchmark-matched papers, then compare evaluation modes in the protocol matrix.

Why This Matters (Expanded)

Why This Matters For Eval Research

  • 22.2% of papers report explicit human-feedback signals, led by critique/edit feedback.
  • simulation environments appears in 25% 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 55.6% of hub papers (5/20); use this cohort for benchmark-matched comparisons.
  • BFCL appears in 44.4% of hub papers (4/20); use this cohort for benchmark-matched comparisons.

Metric Interpretation

  • accuracy is reported in 22.2% of hub papers (2/20); compare with a secondary metric before ranking methods.
  • precision is reported in 22.2% of hub papers (2/20); 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
Brief Is Better: Non-Monotonic Chain-of-Thought Budget Effects in Function-Calling Language Agents

Apr 2, 2026

 Automatic Metrics Not reported Accuracy Not reported
SkillX: Automatically Constructing Skill Knowledge Bases for Agents

Apr 6, 2026

 Automatic Metrics Not reported Task success 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
The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

Jan 19, 2026

 Automatic Metrics Not reported Precision, Latency Not reported
Go-Browse: Training Web Agents with Structured Exploration

Jun 4, 2025

 Simulation Env Not reported Success rate Not reported
Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions

Sep 23, 2025

 Automatic Metrics Not reported Accuracy 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
Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models

Apr 22, 2026

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

Checklist

  • Gap: Papers with explicit human feedback

    Coverage is a replication risk (22.2% 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 (66.7% 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 (44.4% vs 35% target).

Strengths

  • Most papers provide measurable evaluation context (100% benchmarks, 66.7% metrics).
  • 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 (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 BFCL) before comparing methods.
  • Track metric sensitivity by reporting both accuracy and precision.

Recommended Queries

Judge vs Human AgreementBenchmark Slice: WebArenaMetric Slice: accuracyRecent 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)
  • Automatic Metrics (4)
  • Human Eval (1)
  • Llm As Judge (1)

Human Feedback Mix

  • Critique Edit (1)
  • Demonstrations (1)

Top Benchmarks

  • WebArena (5)
  • BFCL (4)
  • OSWorld (2)
  • Interruptbench (1)

Top Metrics

  • Accuracy (2)
  • Precision (2)
  • Cost (1)
  • Latency (1)

Top Papers On This Benchmark

Related Benchmark Hubs

DROP Or BFCL Or WebArena Benchmark Papers BFCL Benchmark Papers BFCL Benchmark Papers (Last 240 Days) BFCL Benchmark Papers (Last 300 Days) BFCL Benchmark Papers (Last 365 Days) WebArena Benchmark Papers GPQA Or BFCL Benchmark Papers (23) HumanEval+ Or BFCL Benchmark Papers (21) MATH-500 Or BFCL Benchmark Papers (25) GPQA Or HumanEval+ Benchmark Papers (22) MATH-500 Or GPQA Benchmark Papers (25) MATH-500 Or HumanEval+ Benchmark Papers (24) MATH-500 Benchmark Papers (15) MMLU Or AIME Or AlpacaEval Benchmark Papers (60) MMLU Or AIME Or BFCL Benchmark Papers (59) GSM8K Or MMLU Or AIME Benchmark Papers (72) MMLU Or AIME Or HotpotQA Benchmark Papers (62) MMLU Or AIME Or HumanEval+ Benchmark Papers (57) MMLU Or AIME Or LiveCodeBench Benchmark Papers (59) MMLU Or AIME Or LongBench Benchmark Papers (59) MMLU Or AIME Or MATH-500 Benchmark Papers (58) MMLU Or AIME Or SWE-bench Benchmark Papers (64) MMLU Or AIME Benchmark Papers (50) GSM8K Or MMLU Or AlpacaEval Benchmark Papers (65)
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