Search papers, claims, runs, and users/

Loading page…

AI is dramatically lowering the cost of reading papers, writing code, and running experiments. But as research output explodes, telling which results can be trusted keeps getting harder. CiteArk connects the claims in scientific papers with their experimental conditions, execution process, result evidence, and verification records, so researchers and agents can verify claims, reuse experimental results, and build follow-up research on them instead of repeating work. We hope these trustworthy research records will grow into a scientific foundation that researchers, labs, and agents can all build on together.

Website

Explore
Claims
Runs
Import a paper

Docs

API docs
Badges & embeds
Roadmap
License Gate

About

About CiteArk
News
Contact & takedown

Legal

Search papers, claims, runs, and users/

ACRFence is classified as partially targeting unknown-safe execution for A1; the proposed attack was validated, but the system was not implemented. · CiteArk

When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent–Tool Boundary

Not assessedPlan blockedFindingclaim-runtime-acrfence

ACRFence is classified as partially targeting unknown-safe execution for A1; the proposed attack was validated, but the system was not implemented.

Source: paper:PDF p. 7, Table 3, ACRFence row; Markdown block p7-b65

Reported and observed measurements

No structured measurement is attached to this Claim.

Assessments (0)

No immutable Assessment has been published for this Claim yet.

Runs (0)

No execution has been linked to this Claim yet.

Research Plan identity

Claim version: sha256:e404a20a04b13d66931b083b0a13fa5128fd0dee3db7748d083c8d6d2a1eb332
Planned experiments: 0
Evidence objects: 0

Assessing partial A1 coverage and the distinction between attack validation and implementation requires a qualitative comparison against the cited ACRFence source under the paper's anomaly definitions. The current numeric parser cannot express that comparison; execution would need the version-identified source and a declared evidence rubric rather than a fabricated scalar.

Machine-readable Claim

Read the Claim and its Assessments as structured JSON through the Agent API.

Open JSON