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ARXIV:2605.09826 · AGENTS · SUBMITTED 12 MAY · 20:15 UTC · FRESHNESS FRESH
ARXIV:2605.09826AGENTSSUBMITTED 12 MAY · 20:15 UTCFRESHNESS FRESHGurusha Juneja · Dylan Lu · Saaket Agashe · Parth Diwane · Edward Gunn · Jayanth Srinivasa · +4 at arXiv
A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs.
Opportunity summary
Pain A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs.
Evidence 0 refs | 0 sources | 0% coverage
Blocker Evidence unverified
A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs. AI agents need the same capacity…
Theory of Mind (ToM), the ability to track others epistemic state, makes humans efficient collaborators. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test literal ToM by asking…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Each task is formally verified for solvability and required epistemic depth, and new tasks are generated increase difficulty as models improve. Code availability is…
Agents moved forward this cycle; last verified May 2026. Public score 7.0/10. Production flags indicate code availability.
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A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs.
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10.48550/arXiv.2605.09826A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs.
Abstract
Theory of Mind (ToM), the ability to track others epistemic state, makes humans efficient collaborators. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test literal ToM by asking direct belief questions. The ability act optimally on implicit beliefs in embodied environments, called functional ToM, remains largely untested. We introduce EnactToM, an evolving benchmark of 300 embodied multi-agent tasks set in a 3D household with partial observability, private information, and constrained communication. Each task is formally verified for solvability and required epistemic depth, and new tasks are generated increase difficulty as models improve. On the hard split, all seven evaluated frontier models score 0.0% Pass^3 on functional task completion, while averaging 45.0% on literal belief probes. Manual analysis traces 93% of sampled failures to epistemic coordination breakdowns such as withheld information, ignored partner constraints, and misallocated messages, providing a concrete target for future work.
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PROBLEM
A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test liter...
METHOD
Theory of Mind (ToM), the ability to track others epistemic state, makes humans efficient collaborators. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test literal ToM by asking direct belief questions.
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Each task is formally verified for solvability and required epistemic depth, and new tasks are generated increase difficulty as models improve. Code availability is flagged in the production record; the p...
WHY NOW
Agents moved forward this cycle; last verified May 2026. Public score 7.0/10. Production flags indicate code availability.
Abstract-backed public claims while anchored extraction refreshes.
A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test literal ToM by asking direct belief questions.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Theory of Mind (ToM), the ability to track others epistemic state, makes humans efficient collaborators. AI agents need the same capacity in multi agent settings, yet existing benchmarks mostly test literal ToM by asking direct belief questions.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Each task is formally verified for solvability and required epistemic depth, and new tasks are generated increase difficulty as models improve. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Agents moved forward this cycle; last verified May 2026. Public score 7.0/10. Production flags indicate code availability.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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A new benchmark for embodied AI agents to test functional theory of mind, revealing significant gaps in current frontier models' ability to coordinate and act on implicit beliefs.
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7.0/10 public viability
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