MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/miroeval-benchmarking-multimodal-deep-research-agents-in-process-and-outcome

stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-03-31
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 56
Source count: 4
Coverage: 83%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

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Canonical ID miroeval-benchmarking-multimodal-deep-research-agents-in-process-and-outcome | Route /signal-canvas/miroeval-benchmarking-multimodal-deep-research-agents-in-process-and-outcome

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curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/miroeval-benchmarking-multimodal-deep-research-agents-in-process-and-outcome

MCP example

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source_context

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  "query": "MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome",
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Evidence Receipt

Route status: building

Claims: 8

References: 56

Proof: Verification pending

Freshness state: computing

Source paper: MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

PDF: https://arxiv.org/pdf/2603.28407v1

Repository: https://github.com/MiroMindAI/MiroEval

Source count: 4

Coverage: 83%

Last proof check: 2026-03-31T20:30:22.298Z

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Ready for execution: MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

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Subject: MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

Verdict

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Last commit

4/6/2026

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Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
Existing benchmarks predominantly assess final reports using fixed rubrics, failing to evaluate the underlying research process.
Implicationpartial
Explicitly stated in the abstract as a core motivation for the work.
Verificationpartial
partial
Evidencepartial
The benchmark comprises 100 tasks (70 text-only, 30 multimodal)
Implicationpartial
Explicitly stated in the abstract and supported by a figure caption.
Verificationpartial
partial
Evidencepartial
process quality serves as a reliable predictor of overall outcome while revealing weaknesses invisible to output-level metrics
Implicationpartial
Directly stated as a principal finding in the abstract.
Verificationpartial
partial
Evidencepartial
multimodal tasks pose substantially greater challenges, with most systems declining by 3 to 10 points.
Implicationpartial
Directly stated as a principal finding in the abstract and analysis excerpt.
Verificationpartial
partial
Evidencepartial
The MiroThinker series achieves the most balanced performance, with MiroThinker-H1 ranking the highest overall in both settings.
Implicationpartial
Directly stated in the abstract as a key result.
Verificationpartial
partial
Evidencepartial
Process-Centric Evaluation audits research trajectories across five intrinsic dimensions—search breadth, analytical depth, progressive refinement, critical thinking, and efficiency
Implicationpartial
Explicitly listed in the parsed section describing the evaluation framework.
Verificationpartial
partial
Evidencepartial
constructed via a dual-path pipeline that supports periodic updates, enabling a live and evolving setting.
Implicationpartial
Directly stated in the abstract as a key feature of the benchmark.
Verificationpartial
partial
Evidencepartial
user-derived queries are consistently harder than auto-generated ones
Implicationpartial
Stated in the analysis excerpt as a finding from further analysis.
Verificationpartial
partial

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MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

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