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ARXIV:2604.27776 · AGENTS · SUBMITTED 01 MAY · 15:04 UTC · FRESHNESS STALE
ARXIV:2604.27776AGENTSSUBMITTED 01 MAY · 15:04 UTCFRESHNESS STALEJinchao Li · Yunxin Li · Chenrui Zhao · Zhenran Xu · Baotian Hu · Min Zhang · arXiv
A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models.
Opportunity summary
Pain A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models.
Evidence 0 refs | 4 sources | 67% coverage
Blocker Evidence unverified
A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models. This overlooks a critical real-world requirement of coordinating across multiple applications to accomplish…
While GUI agents have shown impressive capabilities in common computer-use tasks such as OSWorld, current benchmarks mainly focus on isolated and single-application tasks. This overlooks a critical real-world requirement of coordinating across multiple applications…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Experimental results of leading large models and agents show that: 1) All computer-use agents perform poorly on multi-application tasks (< 21% success rate), far…
Agents moved forward this cycle; last verified May 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.
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mobile layout uses overflow-hidden min-w-0 break-wordsOpportunity summary
Score7.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models.
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Paper Pack
10.48550/arXiv.2604.27776A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models.
Abstract
While GUI agents have shown impressive capabilities in common computer-use tasks such as OSWorld, current benchmarks mainly focus on isolated and single-application tasks. This overlooks a critical real-world requirement of coordinating across multiple applications to accomplish complex profession-specific workflows. To bridge this gap, we present a computer-use benchmark in cross-application workflows, named WindowsWorld, designed to systematically assess GUI Agents on complex multi-step tasks that mirror real-world professional activities. Our methodology uses a multi-agent framework steered by 16 occupations to generate four difficulty-level tasks with intermediate inspection, which are then refined by human review and executed in a simulated environment. The resulting benchmark contains 181 tasks with an average of 5.0 sub-goals across 17 common desktop applications, of which 78% are inherently multi-application. Experimental results of leading large models and agents show that: 1) All computer-use agents perform poorly on multi-application tasks (< 21% success rate), far below the performance of simple single-app tasks; 2) They largely fail at tasks requiring conditional judgment and reasoning across $\geq$ 3 applications, stalling at early sub-goals; 3) Low execution efficiency, where tasks often fail despite far exceeding human step limits. Code, benchmark data, and evaluation resources are available at github.com/HITsz-TMG/WindowsWorld.
Source availability
PDF linkedThe paper record includes a public PDF URL.
Extraction status
Parse run linkedA document parse run is attached to this paper.
Proof status
unverified0 refs; 4 sources; 67% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
Time to MVP
Commercial
Export
Preparing verified analysis
Dimensions overall score 7.0
PROBLEM
A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models. This overlooks a critical real-world requirement of coordinating across multiple applications to accomplis...
METHOD
While GUI agents have shown impressive capabilities in common computer-use tasks such as OSWorld, current benchmarks mainly focus on isolated and single-application tasks. This overlooks a critical real-world requirement of coordinating across multiple applications to accomplish...
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Experimental results of leading large models and agents show that: 1) All computer-use agents perform poorly on multi-application tasks (< 21% success rate), far below the performance of simple single-app...
WHY NOW
Agents moved forward this cycle; last verified May 2026. Public score 7.0/10. Implementation evidence is present through a linked repository.
{"file name": "input.pdf", "number of pages": 20, "author": "Jinchao Li; Yunxin Li; Chenrui Zhao; Zhenran Xu; Baotian Hu; Min Zhang"
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verified
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Concepts
Methods
Materials
Markets
Competitors
A new benchmark for evaluating autonomous GUI agents on complex, cross-application professional workflows, revealing significant performance gaps in current leading models.
Segment
Agents
Adoption evidence
Public code linked for build inspection
Commercial read
7.0/10 public viability
Direct
Adjacent
Substitute
Unknown
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CITED BY
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Extension
Commercially relevant
Conflicting
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2/3 checks · 67%
Build Passport
Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap
status
missing
reason
passport_row_missing
proof status
unverified
cost/budget
No verified cost estimate
confidence low
next verification path
Build brief missing until Build Passport data exists.
Source missing: Build Passport payload.
Experiment plan missing until prototype path is available.
No prototype path attached.
Validation checklist missing until required assets, cost, and regulatory flags are verified.
No checklist artifact is attached to the Build Passport payload.
Derived signals show verified:false until source-backed receipts exist.
Evidence coverage
OpportunityKernel evidence_receipt
0 refs / 4 sources / 67% coverage
stale
Verify missing sources before using this as buyer proof. verified:false
Build readiness
BuildPassport EvidenceState
passport absent
stale
Run Proof Lab or inspect typed missing state. verified:false
Artifact maturity
GitHub and Hugging Face maturity payloads
No public artifact surface observed
stale
Open source artifacts or mark the gap as missing. verified:false
Technical feasibility
partial
Current read
Runnable path is not fully verified.
Evidence
No Build Passport payload attached.
Gaps
Next test
Run minimal reproduction from the Build Passport prototype path.
Market urgency
missing
Current read
Buyer urgency is not verified from source.
Evidence
0 references, 4 sources, 67% evidence coverage.
Gaps
Next test
Collect buyer interview, deployment evidence, or cited demand signal.
Buyer clarity
missing
Current read
No budget owner is verified for this paper.
Evidence
Build tab has no CRM, procurement, or operator source.
Gaps
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Map target operator, economic buyer, and procurement trigger.
Defensibility
missing
Current read
Defensibility signals are missing.
Evidence
No defensibility receipt attached.
Gaps
Next test
Refresh defensibility bars with source receipts.
Integration burden
missing
Current read
No public implementation surface observed.
Evidence
No GitHub or Hugging Face payload attached.
Gaps
Next test
Write integration checklist from prototype path and target workflow.
Capital intensity
missing
Current read
No observed cost estimate is verified.
Evidence
Cost passport has no observed_usd value.
Gaps
Next test
Run cost passport or mark the cost field not applicable.
Regulatory load
missing
Current read
No regulatory classification is attached.
Evidence
Build Passport ledger does not include regulatory flags.
Gaps
Next test
Classify regulatory flags before commercialization planning.
No named scientific founder assigned.
Paper authors are not treated as operators without consent.
People
No named person assigned.
Gaps
Next verification path
Prototype owner missing.
Build Passport does not name an implementer.
People
No named person assigned.
Gaps
Next verification path
Operator workflow not sourced.
No buyer or workflow interview attached.
People
No named person assigned.
Gaps
Next verification path
No GTM owner verified.
No CRM or outreach source attached.
People
No named person assigned.
Gaps
Next verification path
Regulatory need unclassified.
No clinical or regulatory source attached.
People
No named person assigned.
Gaps
Next verification path
ARTIFACTS
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DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
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FORESIGHT
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OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
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COMPETITIVE LANDSCAPE UPDATES
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RELATED PAPER UPDATES
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SIGNAL CANVAS HISTORY AND DELTAS
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TIMELINE
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BUZZ
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