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Paper Citation Record · LEDGER

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security

As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 inbound Pith citation observations for arXiv:2507.22037.

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

pith.paper-citation-record.v1
2507.22037 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:09:39.861497Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T19:19:42.748573Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:19:42.862780Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b6a387b5-4de7-4514-8abe-043f34d44487 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:41.153756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.597452Z digest=sha256:6bfff9c4742d6d11f96fa56dbcff556e309a149813d395f7d521bc8900acf612

Observation 6cd493d6-d804-492f-b72c-8cde5d1c5bb4 · outbound

This paper cites Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.603513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.603513Z digest=sha256:133783126f0bc4bb096862f63cbb4d9747859605e7c7f7f02c46d3dfc00e02cb

Observation 28ac7225-4694-4905-93bc-b1e5a7832ad6 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.609477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.609477Z digest=sha256:60c7d3a2526884f6c17ee077c227ffe36e529b754f41a2eff825ea39f7984327

Observation 99973d18-38bc-4707-9038-dca444a98dd8 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.615039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.615039Z digest=sha256:8524311040a0bd8e46bceb64ec7e7df0e3fd9f6a7ff1e609647dbeb63be85948

Observation cf046c21-fd53-4e9d-b1c2-edb0f1fd98ce · outbound

This paper cites Image Hijacks: Adversarial Images can Control Generative Models at Runtime.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Image Hijacks: Adversarial Images can Control Generative Models at Runtime

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.620116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.620116Z digest=sha256:5e91f4905a583c793a9af496d3851fcdd8057bb2cb81a0c0cb468ac0d9424cad

Observation 9e7c6c50-a605-4ac2-bc77-bee751af0b9d · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:41.137026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.625200Z digest=sha256:d61a452b834e209e9619fc2b8b44c2f3a485090f044ccdddfd1dd3bf006a8b7d

Observation 9cb7fc64-0366-4d19-ab69-4a448b819912 · outbound

This paper cites Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.630560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.630560Z digest=sha256:c012d9f312d59d89d1e06546571730104183b3fc268e66ebf244c49e76ab3533

Observation d005cb89-ec4f-4219-824f-e9cb83aa415a · outbound

This paper cites Stable Reinforcement Learning for Efficient Reasoning.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Stable Reinforcement Learning for Efficient Reasoning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.636062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.636062Z digest=sha256:0304d027475723d3759b1fdc9abef205dbe2249eb324276a055b5330d1b2afd4

Observation 5e243766-bc21-46c4-87c2-c5aa4b25eeaa · outbound

This paper cites From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.641313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.641313Z digest=sha256:5f185819edee5de67017b9bd907b1e377a86f2d6a286fd032731526da7e908e9

Observation b3cf5322-1143-45bb-bd91-3e808b9497c9 · outbound

This paper cites S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models

Reference 10

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unresolved
no resolver link, observed 2026-08-06T12:09:39.647034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.647034Z digest=sha256:449ffaeac0bd68cbb9012603128777534942a9efe581cf69dea643d8b31b6d2f

Observation fc3aa545-c58a-4bb2-bbe2-0c73d2aefbce · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.652963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.652963Z digest=sha256:99b6890a66c2b137aa150f51f87d765418519bc150a29a057e614045197eda47

Observation 048cc48b-0c1b-4b51-9fb7-6c9419701242 · outbound

This paper cites Raft: Reward ranked finetuning for generative foundation model alignment.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Raft: Reward ranked finetuning for generative foundation model alignment

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:09:41.119067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.658398Z digest=sha256:89b569d5357bb07b23fc676a23ccdde0a92b48b8ec75c1c5551336e5a9e0e876

Observation f1e7b308-af24-4d7f-8919-a8b2486c557c · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:41.088483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.663754Z digest=sha256:d6ffdd65154d23e72f6d7cac12f1137bd48b59f3b78c002b7386ab91440a2bd1

Observation ebab30ad-0dee-4a65-835b-e9d800498ce6 · outbound

This paper cites FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.668500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.668500Z digest=sha256:cf5d9cecf2131a675b08b36b8b4c88022c96d924cc4f8114089ff2e87c96cd81

Observation f10d8a88-e333-4fd8-8961-6a1941944a2d · outbound

This paper cites The Llama 3 Herd of Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security The Llama 3 Herd of Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.673979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.673979Z digest=sha256:d13100bd4b32679e1e0d5ce4d3756291e3979a5e56069be30de4f49263b50400

Observation 391f5f5b-1241-4237-970e-1f42eb52cbba · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.679845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.679845Z digest=sha256:682abaf912d44193917b24ef13391919e3ae4c584ff768ffd990aa2bcb10d7ad

Observation 9638a436-a417-4c85-8988-bdbaa52ec948 · outbound

This paper cites The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.684858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.684858Z digest=sha256:924aad9489d2f121b5ee55ac4ccc2f453065210f22cca1481aa0a3400019a87e

Observation 13b317ec-4fe0-4f64-9e4a-ebec3b24439a · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:41.030510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.690601Z digest=sha256:fa1a83e29fec80465dbd8601c19ad8f23f082399ad3d63a80816bf3ea9c91f1a

Observation b88c5562-03a5-4f26-a6b7-0a5c1f784bd3 · outbound

This paper cites Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.696496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.696496Z digest=sha256:3c14f3b1a16748249a7e0a9533dc21cc37aceaed210b43d0874cbcd2f97bc01b

Observation 9bd8b1a0-63cb-4b31-8fdb-9d5ce78d9dac · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:41.008162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.705807Z digest=sha256:8aaa83569dca9a4463ac11817c3da39770d3961d904bc7f0ecc78d28a7f4cb0d

Observation 6b470d80-6eba-4783-a5b4-51126b5557e2 · outbound

This paper cites M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.711544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.711544Z digest=sha256:d3eeb610ab1b7ca032ff887b423e97e0fe7bbfc717b5a8eb7b971ed7ad00bb13

Observation 1126559f-21f4-4e64-83a8-bb3d8b427c5d · outbound

This paper cites Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update

Reference 22

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verified exact
local_arxiv, observed 2026-08-06T12:09:40.121101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.717587Z digest=sha256:23dad59c6e30733201232f0fd6d2ad94581ed0ec3c19debac72e5bfe54dac437

Observation c1538a54-558f-47c4-a7fa-2b01b5e2b5b2 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.984762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.722684Z digest=sha256:e07faa1e16b63c29629aa4b636d177da83c522a6a8409500df8f1d02b612c2b7

Observation be887a7a-fa2c-4f19-b28d-02fa7b34b7ba · outbound

This paper cites A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.727842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.727842Z digest=sha256:aec803ba28905878a2c034e3b88af1280438150dd4e5c1d3d7fecfc7c30bcd27

Observation 126e21bd-5d1b-4911-a812-ea426c438f20 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.965402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.733076Z digest=sha256:2dfdd869155c6f989ec3af0697550b6e053ac7b02fc742de15378eb77e3896a7

Observation e5a05617-9a2e-4ffb-aecd-3053e2d2e054 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.947573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.738380Z digest=sha256:413a23912319293879e88e08e06820e7ad82c3018d78ab9082c313ec9ee43f5e

Observation 311feef7-41c9-4646-bf54-216b3118d6c1 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.930144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.744739Z digest=sha256:6a92258edaa740d8f3679868c4e2e3a65697366a6c0824eca645a1b761c52ac3

Observation 37fa36d3-ee71-4a32-b575-08e9cd19df3f · outbound

This paper cites GPT-4o System Card.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security GPT-4o System Card

Reference 28

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unresolved
no resolver link, observed 2026-08-06T12:09:39.750395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.750395Z digest=sha256:f33de389d78eca731a87cc0616ce970fa1b58e21ceae577c007c711352ae2251

Observation 2755a9e9-8c4c-4ce0-a4b3-b13479b940ad · outbound

This paper cites GPT-4 Technical Report.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security GPT-4 Technical Report

Reference 29

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unresolved
no resolver link, observed 2026-08-06T12:09:39.755271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.755271Z digest=sha256:779b4c6b05246a05095d4fe204238fc06dfad4853943b021f450b47e88020ddf

Observation cc56eb59-3b8a-41f1-af59-ee9a7072c07e · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.911616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.760608Z digest=sha256:1453696b2042d2fbcae02244f0125ec4a2bf8572cfd04734fa0ade779233a7bf

Observation 984ef29e-3279-49d5-b5f9-5b00d303fbf4 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.889233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.765597Z digest=sha256:c5d71ca61ef4bf753d702333f33e4c48bd2a3e747efa9194004be3ec4082a25b

Observation 251e2a50-1a99-44ee-886a-2fe366cfdc72 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 32

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unresolved
no resolver link, observed 2026-08-06T12:09:39.770560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.770560Z digest=sha256:6a517e082f1eb4088ff9a18f30453d3ff604ca13d2bc31208b8c00a2f5572c22

Observation c694ff11-7da1-4ce3-8281-3d35ba53fd74 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Proximal Policy Optimization Algorithms

Reference 33

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unresolved
no resolver link, observed 2026-08-06T12:09:39.776116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.776116Z digest=sha256:b722360b126d68097aac406412eb21289badb5d8998df8526fdf2deaf93a6812

Observation 80dbdf6f-1f6c-4e49-8e18-0adfe99e1857 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.781262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.781262Z digest=sha256:5ba57c7755aadf1398844bbaa273f731c6c9b93f6d70da7fded94e305dc88f89

Observation 66cc0935-f2dc-4ed9-ba1c-8bb7d93b5693 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.857328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.786429Z digest=sha256:4d3486e5815837120b6d2c7e17d346d742828974c3426b2b9259470840877647

Observation e04d1526-a757-4cf2-96b3-9ff0cce7a794 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.791403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.791403Z digest=sha256:d2213b35e3e2053182ad9fbfad9baeb884a98b81f8041c21cb55b839febaad84

Observation 0e9367bb-eedc-43b2-b839-06ff1e3decf3 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.838177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.796557Z digest=sha256:28d44bfd4a26622a70cf3af39cb966ca96939344f4ac4db24692c25c109c9761

Observation f2c1a692-2ea9-47bb-935f-a6eb30891e4d · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.820861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.801981Z digest=sha256:0c3bc3e71771fed9d025870d460e860c631b2ee68e096d948fb13a2ecec229a7

Observation bb329ee2-e590-48a6-99d7-403b4f066f6c · outbound

This paper cites Qwen3 Technical Report.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Qwen3 Technical Report

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.806918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.806918Z digest=sha256:bb8013f57bb420044a08bc19cd03530e5dfce18e0158e11a2d6c5421a10a670c

Observation 84a1fa09-5fac-49a0-9a7c-5d08cfffaf94 · outbound

This paper cites SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.812263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.812263Z digest=sha256:9e4a5c95cba611bcc762c73fabdb1946d9f95b42fe63933a1983019aa4161e3d

Observation 55cf5e45-e9f1-4fbe-bd9f-960173eb29ac · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.817694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.817694Z digest=sha256:35a01c2c23fc0de2a6e4b2d4c18491d13ed1edf3ebd5f851f902a453cb6eaf00

Observation 12053b92-b540-4e4e-b97b-40144ac087cf · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.804480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.823538Z digest=sha256:c521bf93f6cd56c47b6cd2d2f05dbcc08705e8aa29192bbe17d303eefc98398b

Observation b5d488ce-ff01-4ef7-b4b2-c88ba28494c0 · outbound

This paper cites RRHF: Rank Responses to Align Language Models with Human Feedback without tears.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security RRHF: Rank Responses to Align Language Models with Human Feedback without tears

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.829280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.829280Z digest=sha256:2c26071c54b01afefbe7cc1f2aea2d7bd736f6718545a974b3f3ca53803c32e3

Observation d0455717-5695-4dac-8787-f135138ddec6 · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.786415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.835388Z digest=sha256:575340256d4dd14f2349c5dcfc74e03fe4852fd7b4cc82703172844db3103bef

Observation c11f26cd-c1b3-43d3-9d58-d93daf2f6525 · outbound

This paper cites MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.840201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.840201Z digest=sha256:4325bcc50c1714e54136923758222824d508af8bf5d9bb8a284bb49065f064ca

Observation 3edfbbd5-0f3c-4ca0-be8e-eab2ae34accd · outbound

This paper cites an unresolved cited work.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:09:40.730635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T12:09:39.845198Z digest=sha256:9ad606053a55ef27ab0a28bff0ed048a2ea0b5f9e954c758e375c7f83d505190

Observation 2429dbe8-2f4d-407a-ba74-8daf01e091ec · outbound

This paper cites Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.851015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.851015Z digest=sha256:7c7db6b2b195843f92e083633943fbe168bdfb9edea34f2a998e6a7f8c793c68

Observation 7d44697c-bb8e-4e2d-88ff-83c29ccf79f8 · outbound

This paper cites online" 'onlinestring :=.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security online" 'onlinestring :=

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.856064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.856064Z digest=sha256:2558e5078779783dc9ef6758859dea0e7f4f0c36039626b889795092a518b6cc

Observation c58aecf4-3907-4913-85f6-7e6402786a58 · outbound

This paper cites write newline.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security write newline

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T12:09:39.861497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:09:39.861497Z digest=sha256:d38f08d0ed545c17d5a36f0c0107eaa7a6cf7a496a8a6fa977ccfa69058434ab

Pith citing papers

Observation 8d013345-ac84-445d-9291-df68f141e629 · inbound

FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving cites this paper.

FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:19:42.866796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T19:19:42.748573Z digest=sha256:4a61c20e5d2cceb00fb7ac67acd73f76d7e27b502cb3ab8d5b89800dd8753bba

Observation d7297b50-0c44-499a-8b65-3185c59deaa9 · inbound

FedNSAM:Consistency of Local and Global Flatness for Federated Learning cites this paper.

FedNSAM:Consistency of Local and Global Flatness for Federated Learning Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-15T18:46:29.519770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T18:41:54.145958Z digest=sha256:a63fc9fe77fc7822e4df812f73a9fff15bbb04882a0b2ddc0d32e75f6d60982e