Pith. sign in

Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.445328Z digest=sha256:cb0e241520905cf71ef2544ff3a6a9f60d6a49da17ac10723ab8821772a847ae

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.451104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.451104Z digest=sha256:e02d6ffbbb6392b61a3a4d9069e6d9f40fb27f662039aefe512b2982a2e71a0e

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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.455167Z digest=sha256:9336d39b265c0f756eb367b87c1640b75db9644a69d2b358231d7311df4a085c

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.459951Z digest=sha256:6ba5368649b467a18c9071e979df67e4fcc7944e2eed06d12b78a22615438b15

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.464684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.464684Z digest=sha256:45557c36addfc47c732c2137d932801b5006446334601c1dad046af1531aa853

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

Resolution
unresolved
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.469555Z digest=sha256:e510028acbccf709378fd2724000b7145553ccb35c7beffcb694f4a85bdf1bea

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.474192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.474192Z digest=sha256:e1e69ae2e64591dcf434da2aeb39d30a57fd1cf47955dfb819559275b49ce990

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.479277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.479277Z digest=sha256:e645814df0385803a4a01784ee879c2b9ba8b29c432ea41ef21abf5980eac237

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

Resolution
unresolved
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.487952Z digest=sha256:d87d0eb06b1030f8d8543237a8147d0189520b2f88e369e8bca14d102f77bf1a

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

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:13:18.997816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.493080Z digest=sha256:389e0d4c3ef41476715c90561a0d3192a3794f828a817239a84b89c43971b858

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.496854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.496854Z digest=sha256:99078d1ef44492d7892e1eceebf6ce923baa559f6f43787b0c5df8f7d6c37c8b

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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.501699Z digest=sha256:3c4eacf493fd7b449ac167e685aef6181312f02f53328ff2353ef3d0f5862236

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.506544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.506544Z digest=sha256:2a77b8a2ffc6da55f81cdbfac3fec845c1b8f15ac126111963b241a78d39df38

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.510731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.510731Z digest=sha256:7c49be34446dcb1be5453d01d96b878bf8979abfe6b0683c30a5858a82df003b

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.515487Z digest=sha256:22489ac6dd95bcaf5214185be3576be700e2eb5645d792404b2d902101c80803

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

Resolution
unresolved
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.519545Z digest=sha256:8a654989ea0106b9ccb8084dff5e57c28fd2d66bfb8efcdcd40eb106a850d99a

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.523857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.523857Z digest=sha256:a5d995d0a7e330e5958c54cb4dfd984a1c8d1915446c034eebbc8f3521a45c26

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.528756Z digest=sha256:96d818c9656f3bb427d53116f8d54285a14699116859d91b260caa2979cf3e93

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.533843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.533843Z digest=sha256:08fa1492cd337ebccaccb92ed055623d69bad6cddf74985255400d791882659e

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

Resolution
unresolved
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:eb9dc43aedd35eaa41c5001e47875103f8760304ce08544f9fbb252632632f8c

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.543353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.543353Z digest=sha256:0a6bb6e22c0541fe5a6d0b766cad80caf8c9fabdb8f10d449d185b038c9660af

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.547912Z digest=sha256:c5d60c5049b7bf10a830f5e594693999e2c3de42f8eb9940e4465dae7c18feb8

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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.556082Z digest=sha256:6619582597e3fe10946b06f6c0783e11c0ebe4010ee98d01b730e683c60de842

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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.560507Z digest=sha256:8b5ed5ccee3acef82b234233301488fc2e24580b8b39f81e34d483b18e3c8aaa

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

Resolution
unresolved
raw_fallback, observed 2026-08-11T13:13:18.880979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.564624Z digest=sha256:e9255f29b683a6d7962c34aa1359b95f5f56b15e85626ac6737fa5e5a3c86040

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

Resolution
unresolved
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=sha256:94a0f2dbc473a236e3c5cfad4a88eaf6426ffd8c275295b0720865a41e59a103

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.572004Z digest=sha256:a3e487d72460b2cb7332a98927e1d659922dbd0706685c3ff4e7bfc8ee48d9ea

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

Resolution
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.576276Z digest=sha256:a088f4932cb26f0dee943aed046ab78e8f21b390797ce46d829c33386915df05

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

Resolution
unresolved
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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T13:13:18.580963Z digest=sha256:b5bca701af3ac15cbb4096d065145ffaf1f612e8149b8954d2a8a5b684daefd7

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

Resolution
unresolved
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=sha256:0c335b82a6a856e01f64b5136a9d6fcd073942d03e1d9d55f07fb63574cdf840

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

Resolution
unresolved
no resolver link, observed 2026-08-11T13:13:18.590426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:13:18.590426Z digest=sha256:fedb74d64264bec1b2cce93371188aa5c8faee3145b30d47709a64b919f0a60a

Pith citing papers

No inbound Pith citation observations are available.