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ARXIV:2606.03686 · EMBODIED AI AGENTS · SUBMITTED 03 JUN · 20:42 UTC · FRESHNESS FRESH
ARXIV:2606.03686EMBODIED AI AGENTSSUBMITTED 03 JUN · 20:42 UTCFRESHNESS FRESHSarah Barrington · Maty Bohacek · Hany Farid · arXiv
A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content.
Opportunity summary
Pain A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content. We use this dataset to evaluate the automatic forensic identification (audio, video, or text) of AI agents,…
We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We use this dataset to evaluate the automatic forensic identification (audio, video,…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. We also contribute a scalable data-capture system that creates agents, automatically pairs them with human crowd workers, records audiovisual conversations across specified scenarios, and…
Embodied AI Agents moved forward this cycle; last verified June 2026. Public score 7.0/10. Production flags indicate code availability.
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Score7.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content.
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Paper Pack
10.48550/arXiv.2606.03686A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content.
Abstract
We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We use this dataset to evaluate the automatic forensic identification (audio, video, or text) of AI agents, study the nature of human-agent interactions, and provide a benchmark for future advances in the large-language models and AI-generated voices and faces that power embodied AI agents. We also contribute a scalable data-capture system that creates agents, automatically pairs them with human crowd workers, records audiovisual conversations across specified scenarios, and identifies and separates the human and agent in the combined stream.
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; 3 sources; 50% 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 dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content. We use this dataset to evaluate the automatic forensic identification (audio, video, or text) of AI agents, study the nature of human-agent interactions...
METHOD
We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We use this dataset to evaluate the automatic forensic identification (audio, video, or text) of AI agents, study the nature of h...
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. We also contribute a scalable data-capture system that creates agents, automatically pairs them with human crowd workers, records audiovisual conversations across specified scenarios, and identifies and s...
WHY NOW
Embodied AI Agents moved forward this cycle; last verified June 2026. Public score 7.0/10. Production flags indicate code availability.
{"file name": "input.pdf", "number of pages": 15, "author": "Sarah Barrington; Maty Bohacek; Hany Farid", "title": "The DeepSpeak-Agentic Dataset", "creation date": null, "modification date": null, "kids": []}
Implication not extracted yet.
partial
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Concepts
Methods
Materials
Markets
Competitors
A new dataset and capture system for evaluating and studying human-AI agent interactions and identifying AI-generated content.
Segment
Embodied AI Agents
Adoption evidence
No public code link in the paper record yet
Commercial read
7.0/10 public viability
Direct
Adjacent
Substitute
Unknown
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Hacker News
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Bluesky
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CITED BY
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Foundation
Extension
Commercially relevant
Conflicting
Owned Distribution
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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 / 3 sources / 50% coverage
fresh
Verify missing sources before using this as buyer proof. verified:false
Build readiness
BuildPassport EvidenceState
passport absent
fresh
Run Proof Lab or inspect typed missing state. verified:false
Artifact maturity
GitHub and Hugging Face maturity payloads
No public artifact surface observed
fresh
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, 3 sources, 50% 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
Next test
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
No public artifacts yet.
DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
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FORESIGHT
No prediction yet — minted on next Foresight batch.
OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
No verified OpportunityKernel changes since the last view.
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
Buzz trend pending.