Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2311.02782.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:20:57.370815Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T11:54:38.318598Z
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 6240f525-8b5d-4ed4-9fc1-efddc6d9993e · inbound
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:20:57.370815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1a2226f-13a8-47df-b020-48b14c39ec3a · inbound
Foundation Models and Transformers for Anomaly Detection: A Survey cites this paper.
Foundation Models and Transformers for Anomaly Detection: A Survey Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:32:49.214107Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e277ee4-4324-4251-977e-67a81fa83a6b · 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 Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T00:53:23.020697Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 822384a5-c1be-49f2-b17a-e430b35e14ce · inbound
IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning cites this paper.
IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:20:12.317577Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4458cc4b-21e3-4c61-9392-4f918c64025d · 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 Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T11:55:33.284392Z
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.
Observation 58bd90a8-ecad-48ac-976a-f6ea1e16bc2c · inbound
MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models cites this paper.
MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:46:00.818492Z
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.
Observation 158bb9dc-f5ad-4b3d-8f31-63f2a1266f2b · inbound
Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent cites this paper.
Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T11:54:38.321005Z
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.
Observation 6f64f4e8-e456-42d9-bc5a-3377813b5579 · inbound
RobustMAD: Evaluating Real-World Robustness of Multimodal Small Language Models for Deployable Anomaly Detection Assistants cites this paper.
RobustMAD: Evaluating Real-World Robustness of Multimodal Small Language Models for Deployable Anomaly Detection Assistants Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:56:12.376403Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.