arXiv:2608. 10300v1 Announce Type: new Abstract: Electronic health-record interoperability is a boundary problem: legacy systems, generative models, terminology services, identity systems, and human reviewers may each expose rich internal states, while operational exchange requires a narrow shared interface of typed claims, bounded uncertainty, provenance, and explicit admission or abstention.
By Alvin Spivey, Thomas Huang
arXiv:2606. 27593v1 Announce Type: new Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries: building-block architectural components that specify a cover of local contexts, local representation families, restriction maps, gluing rules, obstruction policies, update obligations, and human-facing views.
By Sridhar Mahadevan
The paper introduces a claim‑anchored execution contract that binds a tool‑using agent’s emitted claim to its exact source span, the ordered execution prefix that produced it, and the source version and access state observed. Each receipt contains deterministic anchors, source identifiers, offsets, hashes, quotes, and a domain‑separated execution commitment, allowing a verifier to reconstruct these bindings before semantic or task labels are joined. The contract defines seven independently testable properties and demonstrates high detection rates against cross‑object attacks, with strong performance on conflict‑aware support guard evaluations.
By Miaobo Hu, Shuhao Hu, Xiaobo Guo, Xin Wang, Bokun Wang, Yina Sa, Daren Zha, Jun Xiao
arXiv:2608. 07946v1 Announce Type: cross Abstract: Text-to-SQL benchmarks ship schemas whose column names already say what the columns mean.
By Mike Helwig
arXiv:2607. 04735v1 Announce Type: cross Abstract: When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two globally consistent worlds can agree on every shared attribute yet disagree on the query answer.
By Ratan Bahadur Thapa, Daniel Hern\'andez
The paper reports that a model can pass fidelity checks—verifying that extracted values match the source—without actually opening a datasheet, due to a hidden constraint that disables tool use. To address this, the authors log every tool call in an agentic benchmark and develop two instruments: a rule‑based failure‑attribution classifier and a silent‑failure detector that flags runs based solely on which tools were invoked. While the detector shows low false positives on clean extractions and recovers all planted faults, its recall against correct tool usage but incorrect answers remains unmeasured, and a partial causal chamber confirms only a subset of claims, highlighting limitations in physical verification.
By Qing Ye, Meng-Hsuan Lin
arXiv:2608. 02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose combined execution contract remains external.
By Dongxu Yang, Ziyi Liang
arXiv:2608.21418v1 Announce Type: new
Abstract: Manufacturing knowledge graphs that integrate data from heterogeneous industrial systems face a trust deficit: consumers cannot determine whether queri...
By Grama Chethan
arXiv:2606. 17529v1 Announce Type: cross Abstract: Scientific machine-learning (SciML) surrogates approximate expensive simulations, but exact expected outputs for arbitrary inputs are unavailable (the oracle problem).
By Meng Li, Xiaohua Yang, Jie Liu, Shiyu Yan
arXiv:2608. 04457v1 Announce Type: cross Abstract: As "AI Scientists" emerge to drive research via the Model Context Protocol (MCP), systems relying on ephemeral scripts will fail.
By Hans-Martin Will, Allen L. Brown Jr., Matthew Fuchs
CARGO is a framework for evaluating agentic AI systems in production that addresses the problem of reference-instance divergence (RID), where reference-based judges penalize correct answers that involve different entity identifiers. It treats retrieved references as procedural exemplars, grounds judgments in the live instance’s context, assigns a three-way status to claims, and gates evaluation by retrieval confidence. Using the CARGO-Bench diagnostic suite, CARGO eliminates false penalties and improves discrimination while revealing a limitation in detecting procedural corruptions.
By Mukul Chhabra, Shail Patel, Luigi Medrano
AmaraSpatial-10K is a curated collection of 10,071 synthetic 3D assets that are metric‑scaled, deterministically anchored, and accompanied by PBR maps, collision hulls, reference images, and multi‑sentence metadata. The dataset is paired with an evaluation suite that includes a Scale Plausibility Score, Concept Density metric, anchor‑error auditing, and a CLIP coherence protocol, and it outperforms existing collections such as Objaverse in CLIP Recall@5, stability in Habitat‑Sim, and human preference in scene placement. The authors also demonstrate that richer descriptions drive the retrieval gains observed.
whyItMatters":"The dataset and evaluation tools directly address common defects in large 3D asset collections, enabling more reliable use in embodied AI, robotics, and spatial computing applications."
By Mohammad Sadegh Salehi, Alexander J. P. Perkins, Igor Pardo Maurell, Ashkan Dabbagh, Raymond Wong