Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.12749.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:01.001056Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T15:09:54.989983Z
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 bee0c231-17ff-4248-bb05-7bb698b8d753 · inbound
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:21:01.001056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b5a060a-d28d-4eb4-badc-1a12c134e530 · 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 LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:40:09.026068Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 582b06f0-c6b8-4f8c-9ee4-dce130ab28a6 · inbound
AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation cites this paper.
AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T22:01:17.990247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0b1bbaf2-e69b-4345-a474-1f62516f1030 · inbound
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
Reference 190
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:09:54.991615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b1316c37-e075-42be-9718-abd6fdeffef2 · inbound
Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection cites this paper.
Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T23:45:43.436443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.