Pith. sign in

Paper Citation Record · LEDGER

AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2504.11914.

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

pith.paper-citation-record.v1
2504.11914 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:54:46.885915Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.046405Z

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 e6bd7a1a-c41f-4282-8fd8-063aba9a75ea · inbound

LR-IAD:Mask-Free Industrial Anomaly Detection with Logical Reasoning cites this paper.

LR-IAD:Mask-Free Industrial Anomaly Detection with Logical Reasoning AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T05:54:46.885915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:54:46.885915Z digest=sha256:61eb1b8a327430b19ae7849eec504dc236b1328c3e272b830dd8f18b43640926

Observation 3355f90a-119c-437b-b7bb-838314bc3c59 · inbound

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

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:57.635131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:57.635131Z digest=sha256:0e5022218ed45f687306175560bb1dc018ed3d9ebc351e8c1e355836b89c7717

Observation a9db3fcc-f3cb-4f5c-a685-2d35d9a36ffb · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T12:40:08.901123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:40:08.901123Z digest=sha256:40bfeb3416604236ebf08ceb4f1e8727c859e54dd99b927d02e6e8527138e6bb

Observation d457a7fd-5db9-4127-adfc-e19a8219c197 · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T00:53:23.177487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:53:23.177487Z digest=sha256:d36e4ac57f90e201b31b32a22172b82bff681678ef05478deef4cff2670c7405

Observation 326df01e-f706-4a4e-93c2-d7492378f89c · inbound

AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation cites this paper.

AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T22:01:17.992892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T21:58:58.999285Z digest=sha256:6e32f91173e58adfc77ff4d8a110f27870d7ba5964158329ae0910200e01c86c

Observation db978b2a-e1e2-4eea-b2ef-c9ce2758cf0d · inbound

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning cites this paper.

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:10:32.047937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T03:08:58.617137Z digest=sha256:6a7b78af3f291c5cd7eddd26cab5a640783ec130efb623e1e66a9e9165592ec2

Observation b4e16b81-f00d-443d-834b-d4bdea4e2d0e · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-15T21:06:38.120879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T21:05:11.117495Z digest=sha256:0c0677c60059613fcf4abd47bbe5dab68e8b1b020968080921ba04beeced4fb4

Observation ce5c55d0-bbaf-4405-816d-7eab6fcf94d4 · inbound

Topo-R1: Detecting Topological Anomalies via Vision-Language Models cites this paper.

Topo-R1: Detecting Topological Anomalies via Vision-Language Models AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T11:45:32.867019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T11:41:27.021776Z digest=sha256:237f750d338acbc2860982f8fad363d20b7f923ff56959c71912946b89e7805a

Observation b03a3b66-eb1a-4d44-bd3f-da79f8cc604f · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-15T11:55:33.344038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T11:54:18.587529Z digest=sha256:4979e7704b5f32efb896638b3255bc4907a574c72e8aed7e25ccfb399b5f0744

Observation 24d9801a-6a0b-4eb9-bc46-6c35e92ff2c0 · inbound

MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection cites this paper.

MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:36:26.485832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T05:07:29.463188Z digest=sha256:bc9218601ba771f9dfe97ef5ca61ecc5d7b13723e25bb3cddbbc7f9b38cc76db

Observation 13b48f17-1f37-42e4-9598-b2361b0c68c0 · inbound

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools cites this paper.

IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:33:58.466776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T05:33:30.670201Z digest=sha256:406b361c0fb71c4152138cf85d50f95e428077c568728b6d50b67eecde62e7b0

Observation 29efe57e-9b06-4554-8462-b1ef55882ff3 · inbound

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection cites this paper.

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-29T08:13:14.934769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T08:10:15.306343Z digest=sha256:e9686b40a5c3f8beaf53e57c33c220dcb2c427e9970c793fc7f83273377c945f

Observation 95463d59-62e4-43a4-948d-f7756b2f49bc · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 188

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.048657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:98b22359bcb5b45807318cdc2e7585584619583cdb724bc22bcdda51493e139f

Observation a16fb88a-b39b-4ada-bf8e-992670bfa17f · inbound

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection cites this paper.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:01:58.407747Z digest=sha256:3405ed6b3e5a8b25e6b2f8c4dd63a32e250c1bf18fa75b02c7b84959697ad216

Observation e65fb628-7059-4772-a0e7-37e12e3e0ed3 · 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 AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-11T23:45:43.436443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:45:43.436443Z digest=sha256:b03ad8dfa9036a298b516ffab105f984c78f2cfbc06a3d01401069374390a683

Observation 52aec8ab-a827-4325-8f4c-7fca298a2578 · inbound

ADOPD: Reference-Privileged On-Policy Distillation for MLLM-Based Industrial Anomaly Detection cites this paper.

ADOPD: Reference-Privileged On-Policy Distillation for MLLM-Based Industrial Anomaly Detection AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T10:50:50.660622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:50:50.660622Z digest=sha256:172430473c3ef375a000a57dc355e213cfbebfd884e3c407e2fbdaed2e23f73f