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Paper Citation Record · LEDGER

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models

As of 12 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.16213.

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

pith.paper-citation-record.v1
2412.16213 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:13:18.590426Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d157691-cb7b-4a34-b66c-657448e0234c · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 1

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unresolved
raw_fallback, observed 2026-08-11T13:13:19.042257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation cd3509cf-ff48-44a9-addb-49e4f2856bb7 · outbound

This paper cites Synthesizing Robust Adversarial Examples.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Synthesizing Robust Adversarial Examples

Reference 2

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source=arxiv_source observed=2026-08-11T13:13:18.451104Z digest=sha256:0f01cf6c4b4afbd359669907332af4e9569e3b243c0ec63114790d05eeeba835

Observation f3d7c113-4aa4-440b-a08b-a30447b9bcc3 · outbound

This paper cites Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks

Reference 3

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verified exact
local_arxiv, observed 2026-08-11T13:13:18.786620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.455167Z digest=sha256:668567cbc359a23eefa319e71107ffc8de3ab32afd1a934bca219b680bfad32a

Observation 241e4e68-5e96-4a23-b20f-457e19b444ca · outbound

This paper cites Boosting Adversarial Attacks with Momentum.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Boosting Adversarial Attacks with Momentum

Reference 4

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no resolver link, observed 2026-08-11T13:13:18.459951Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-11T13:13:18.459951Z digest=sha256:1babf4574dbf088273c073c6580c95939749a33dde9bfa78bb9a0e7478eab036

Observation 3de9ea00-e4ce-4770-ae3d-69b1def32de4 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.464684Z digest=sha256:d538bec1ec326141ba0de980e66454f1c7c88398db62c0fef72a3b5365a5090f

Observation e9662292-8edd-46a0-a179-75ad07ab14a9 · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 6

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raw_fallback, observed 2026-08-11T13:13:19.027863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation ca6f294b-5500-4dde-9ab7-b2dacd7096e9 · outbound

This paper cites Deep Spatial Autoencoders for Visuomotor Learning.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Deep Spatial Autoencoders for Visuomotor Learning

Reference 7

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source=arxiv_source observed=2026-08-11T13:13:18.474192Z digest=sha256:c09bdd4f1d1197bf41a0055a21603c18e169e6f2d155576406afce11645ed726

Observation bcde7769-85b3-4cdb-819f-e24aff66f0fa · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Explaining and Harnessing Adversarial Examples

Reference 8

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source=arxiv_source observed=2026-08-11T13:13:18.479277Z digest=sha256:de4d30be540a1e20e6b916eb20a1bb3abddce73c851a5c3f1b47510578ee15e1

Observation 66c26f92-5666-49b4-bca4-509470ea4404 · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 9

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raw_fallback, observed 2026-08-11T13:13:19.012368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.487952Z digest=sha256:f80ae33d102b1706b0ef1eb16a329baea9725e09a76cd2a2bc3333aafa954a3c

Observation 11d23801-668f-4d7b-862d-b3ea407321d4 · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.493080Z digest=sha256:e5bb491dc2ed6db4c1be75020a61d7e3801f6fb76d5abf7555bb3ded111bee3d

Observation 4175eedb-ba3b-47a8-90b6-f7ba8854b81e · outbound

This paper cites Towards Transferable Targeted 3D Adversarial Attack in the Physical World.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Towards Transferable Targeted 3D Adversarial Attack in the Physical World

Reference 11

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source=arxiv_source observed=2026-08-11T13:13:18.496854Z digest=sha256:19049dbac96bc5b2b0d4222db153d1b3e23e5a00e2728ab5b8b38c6f476bbfe0

Observation 428515a0-2775-4ecd-8283-ba33f41e2261 · outbound

This paper cites D.; Wang, Z.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models D.; Wang, Z

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-11T13:13:18.981742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.501699Z digest=sha256:0399b7eab21812a64e40f67134398eec5f62ef4e6f8032fbaa79f209c6ffdfda

Observation 802f7954-ed27-4922-8ef7-246900b7c4fd · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.506544Z digest=sha256:e45889b33f10a23930a6bc208307ffa9d7b9f5a2915cca969ed2ee77f1dfc19e

Observation 375d866b-7e54-4b62-a38a-4ed4fa586753 · outbound

This paper cites Adversarial examples in the physical world.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Adversarial examples in the physical world

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.510731Z digest=sha256:ad7157a19ef6ab7763d16fa908d68151558de7d99be549deed79ad023622bdd9

Observation d2e969cc-bb68-41ae-b99f-79fffde10a47 · outbound

This paper cites Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF

Reference 15

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no resolver link, observed 2026-08-11T13:13:18.515487Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.515487Z digest=sha256:bbda547b61486da94884bf7a695330025d91aba5b120d69d4cf2a4ce0dc9db87

Observation 708d5c0a-684b-44dd-8734-b4cdbe1a3d2a · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 16

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raw_fallback, observed 2026-08-11T13:13:18.956589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.519545Z digest=sha256:d7f9496b0db033645b352b211072560a759ee57ecb4a446170e9894501b03eda

Observation f259b160-b635-41bd-aca7-68bd6a56cb1a · outbound

This paper cites Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.523857Z digest=sha256:618793c6a35631f7a7cd027b5e68476d79747ddc3df26236a26b0de748a8a1af

Observation 69afe7f7-2050-454b-8a49-89b22e23353c · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 18

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no resolver link, observed 2026-08-11T13:13:18.528756Z

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source=arxiv_source observed=2026-08-11T13:13:18.528756Z digest=sha256:97b00e222fe88d0dcfffde57216ccf146f8ba0342d48b52345d760d5354527cd

Observation df43019d-0f6a-4675-b6c5-2d83ebd2c023 · outbound

This paper cites P.; Tancik, M.; Barron, J.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models P.; Tancik, M.; Barron, J

Reference 19

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.533843Z digest=sha256:939e7a0c1f81418e8449f9ab46ed6275252d65277c477fbb4f3d3c4f060e6a63

Observation b57cfa9b-9e9c-432b-97e2-67ef007358dd · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 20

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no resolver link, observed 2026-08-11T13:13:18.538615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.538615Z digest=sha256:9b5dc6078f392f81daa33f58ccd8a31b9f8839ddb8cf9ac1271fd4fdcc52b8d5

Observation 2ba2a0d9-3f76-420e-8851-62c72a0a089d · outbound

This paper cites W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.543353Z digest=sha256:f4d1bc6fc1a61455d1d7ee353e45ec2686e9321dbb64dcd9bdd31a5c7d6ad02b

Observation 492d4c23-f90c-4871-8705-53818a8791e4 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models SAM 2: Segment Anything in Images and Videos

Reference 22

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no resolver link, observed 2026-08-11T13:13:18.547912Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.547912Z digest=sha256:3e0822d63224f4caf78e42b7a74271884956698c63f8756d906b1864b610b03a

Observation cb5e6082-7cd3-4247-84a1-0ad1ae05a8ee · outbound

This paper cites J.; and Jamali, M.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models J.; and Jamali, M

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-11T13:13:18.914741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.556082Z digest=sha256:0c346756b11b3559a02c8b8e5544939da2bb2e29533b332800fa319da3c052a5

Observation b5edd65b-2a51-4310-9d82-4bb83978ae76 · outbound

This paper cites R.; Mousavi, S.; Ghorbanpour, S.; Gundecha, V.; Gutierrez, R.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models R.; Mousavi, S.; Ghorbanpour, S.; Gundecha, V.; Gutierrez, R

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-11T13:13:18.900287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.560507Z digest=sha256:19c4ee30b29dab51557f96ae3ce591abc96d063b3718a37761aa5dce6b40b008

Observation 784204e0-ce72-4b11-ab1b-1eb1661139ef · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.564624Z digest=sha256:6f251122c30b0d145e8580f5afb890067ea7501344521d8ea19426d7bb5461f4

Observation 44e45304-e94c-429a-ae6e-15de1c42ea59 · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 26

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no resolver link, observed 2026-08-11T13:13:18.568385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.568385Z digest=sha256:3b3e3260a25cfebf623fb3a355fc10227724dff9d09b17054b5c3676286660ae

Observation 4e92a32b-5607-4824-96ee-fbe324e54809 · outbound

This paper cites Adversarial T-shirt! Evading Person Detectors in A Physical World.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Adversarial T-shirt! Evading Person Detectors in A Physical World

Reference 27

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no resolver link, observed 2026-08-11T13:13:18.572004Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.572004Z digest=sha256:0f65a5afab17a33c9ff6045c1aa0ff0bdb6303ca4cf6c278edc981362c1e29f9

Observation ee85b270-a9e6-4940-8db5-99c7416a1b3b · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-11T13:13:18.859204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 3f505dcc-6a5a-4be6-bd2c-f1b438ab005c · outbound

This paper cites an unresolved cited work.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-11T13:13:18.844225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.580963Z digest=sha256:4fe3de6a272b4e2386d12212db2dc6ff0f1c52ccb6850bbcdc649d38a0fd807a

Observation 395aad5c-5bed-437e-ae06-f924d8eb9e1d · outbound

This paper cites , " * write output.state after.block = add.period write newline.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models , " * write output.state after.block = add.period write newline

Reference 30

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no resolver link, observed 2026-08-11T13:13:18.585513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.585513Z digest=sha256:6fc61ff5ef04ae19aba07a1afeb0acd998c2908bd75a4b50a4b1285f5c22dd94

Observation b29280b9-a9d8-4789-be04-38d22937c5a1 · outbound

This paper cites write newline.

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models write newline

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.590426Z digest=sha256:2bd1ee4ff3608f2f027547170752a640d08ce602a5787b8a64e4ce77039de912

Pith citing papers

No inbound Pith citation observations are available.