Paper Citation Record · LEDGER

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2501.15795.

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

pith.paper-citation-record.v1
2501.15795 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:20:58.030616Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T21:06:38.124724Z

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 bf93753c-c81c-4d61-aa73-993475a430bb · inbound

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:58.030616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57437c8c-ddc2-45a8-aa45-aa22c5afefaa · inbound

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation cites this paper.

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:42.623068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34e8e425-fae2-4883-8d95-e557d56e9e67 · inbound

EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO cites this paper.

EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T12:40:08.912929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 570ebd84-7f3b-4f71-8ff5-5ed22a4e5b9e · inbound

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization cites this paper.

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T00:53:23.322660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 077587d2-98f8-4071-8f38-d87d8f1a3d28 · inbound

PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments cites this paper.

PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T18:34:02.796027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a56f7b-1f65-4fe5-92af-3c0f359d48f2 · inbound

EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models cites this paper.

EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:06:38.126298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56ee13e5-42b9-42e2-9c4c-95dc813bfed1 · inbound

AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison cites this paper.

AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:55:33.332412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.