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Paper Citation Record · LEDGER

MVTamperBench: Evaluating Robustness of Vision-Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.19794.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.19794 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:52:26.868304Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T11:35:22.079359Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d0965ad8-1162-4095-8b4a-402b8dc9755b · inbound

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use cites this paper.

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use MVTamperBench: Evaluating Robustness of Vision-Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:52:26.868304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:52:26.868304Z digest=sha256:2828fba62db11da698dd5494d24c64e75b96a6dae439a46ebc6246e2c0f84fab

Observation 5dd96b18-3fdd-4fa9-bbb0-d3ab618310f8 · inbound

Hybrid AI for Responsive Multi-Turn Online Conversations with Novel Dynamic Routing and Feedback Adaptation cites this paper.

Hybrid AI for Responsive Multi-Turn Online Conversations with Novel Dynamic Routing and Feedback Adaptation MVTamperBench: Evaluating Robustness of Vision-Language Models

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:35:22.191813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:35:14.909944Z digest=sha256:4ab891519a4fc98bcaf3e51effbd3317e4077fe8161ed0c66f8fe201fb3086c3