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Paper Citation Record · LEDGER

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems

As of 16 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 0 inbound Pith citation observations for arXiv:2607.06807.

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

pith.paper-citation-record.v1
2607.06807 v1

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T20:55:21.031591Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

79 of 79 outbound references displayed

  • verified exact2
  • verified fuzzy37
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch35

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 96788680-c4c1-4db7-8808-e02a60b70f6c · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Gemini: A Family of Highly Capable Multimodal Models

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.995323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c016dcac8aaa49076943b183b86f3f58431ab56251a0413275c00b204d5b57d9

Observation ac7258ce-13a5-4b1f-afb2-b9be6f1ba4c1 · outbound

This paper cites Qwen Technical Report.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Qwen Technical Report

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:35.029686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:87675ca84c7b6a49617296ed62418366df370d6851b26e33d379318d16d9093a

Observation b276e316-fdb6-4c6d-98ae-cc019be49b72 · outbound

This paper cites DeepSeek-V3 Technical Report.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems DeepSeek-V3 Technical Report

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.828909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:345c187f6e8997191ced9e47f7fa9fa5d2102470b964c95b29ef01d89c46c894

Observation ff2b41a1-8d09-4d1d-b67a-523acb272037 · outbound

This paper cites Frontiers of Computer Science , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Frontiers of Computer Science , volume=

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.968241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:9d0cc0d7bba5abb7439a44ba4893a0556707dbe69378de20836cb2df571f8b2f

Observation d3be19a4-7216-4ba6-a281-2919442ef2e2 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.914835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:4c61e766a1c76d23fe87f5db60b4abc34faf1346c9f5ed5ae0642e6081108a91

Observation 87a92a94-adc6-4ae9-a189-0a8493770a5c · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Advances in Neural Information Processing Systems , volume=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.937825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:37003c947eb5c192ce641e54d17c8837f283de0662be89fea756160cde5698af

Observation cbc9cc4c-73a1-4fc3-8b88-e49e4362b092 · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Forty-first International Conference on Machine Learning , year=

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.537088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:7e957cf6d186c3248b3958a8abe323d1b6dfa5f51c7e4bc8105f67939ce70e8d

Observation 6bfcbace-c70b-442f-a65c-aed5ad95e5ba · outbound

This paper cites Scaling Large Language Model-based Multi-Agent Collaboration.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Scaling Large Language Model-based Multi-Agent Collaboration

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.580097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:dd12251f79158a8c8224fe368491cfe9deba533903bb49c4c00b0f8d4a70106c

Observation 4b0e31d7-37d7-4263-b851-d33160c57eae · outbound

This paper cites author=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems author=

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.652640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:317fb82a30e17edef4f2265dd9d3d757022000aa1db9f8e93bb216a6663d9236

Observation 2957c9cd-ab30-4d67-85c2-1c1fcf7162b1 · outbound

This paper cites Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.220087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:bb4b453f1fae57aed95bb4108425d4ca5e9ac17d7fc58e9ab6f1ce121786e030

Observation b985f25c-b7c3-46ca-9007-06eadf48fdb2 · outbound

This paper cites 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) , pages=

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.229297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f4e9042b1ff1b6c5c3ca2c1a71a8cd6234708c1a2321024cedf91a860a155a4b

Observation fbf3cfad-54c3-4069-871a-63b61fc40a6a · outbound

This paper cites DeepInception: Hypnotize Large Language Model to Be Jailbreaker.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.622539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:a97731149e075b3e2a0d203686496472b9bd5b0e1c9dad0160276c76e73eeddd

Observation 5ab3aae1-2637-44a4-9263-91c0d68b1018 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.969333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:365363318ba1d4fc428cd9720e025950a19c5a9a2f8f0c8729f81867047aeff7

Observation a6478b69-8110-4f00-9e8e-b95600c45bc3 · outbound

This paper cites RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.974946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8a1f67cdd93b7ba43a545fcf40f3d07a436901eb7c373d6c8f247035265db13c

Observation e57bf030-f21d-445d-82d9-05dc65abec5c · outbound

This paper cites Findings of the Association for Computational Linguistics ACL 2024 , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Findings of the Association for Computational Linguistics ACL 2024 , pages=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.000678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:dbfabac0fe46277dc08f2d66fb521af2dd898f803d0082c6f2b6677d8ff6bc3d

Observation a19b7883-5357-4b5f-a4de-341be8b0f687 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Advances in Neural Information Processing Systems , volume=

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.895527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:cdcea55f2f0b1c8899e6a69c7142ac6ebaab0b3ffff4125a763721ab413e2e8b

Observation 4378fb33-7fba-4141-8afe-b42e1254040a · outbound

This paper cites Get my drift? Catching LLM Task Drift with Activation Deltas.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Get my drift? Catching LLM Task Drift with Activation Deltas

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.851213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:85e6fe19990010b0e9b598aa13e037c6c7748928a26ed40b3671bb430cd733e1

Observation 84cdd8e4-2e1a-4b30-8360-17e31f7ae762 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.919538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:af0feea93b8c43deb6983a04fc88edd0477c2b8dde48f6bfc68dc34851a90e71

Observation e6e9c041-3718-4108-b816-5722b6a777f5 · outbound

This paper cites JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.916124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:24eb8c43bd201ac8090fc7aae8dc1a1fad915c832cc16a36d23a365aa5339941

Observation d3520720-f9ab-4df1-9c89-01ffc474de57 · outbound

This paper cites an unresolved cited work.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:57:35.945343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:210341cb6f8f89a08084783c9e9cf94852c02746a651bfe323b7efd917c2982c

Observation fe3a04f6-c054-4b93-a85e-4153e2764802 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Training Verifiers to Solve Math Word Problems

Reference 21

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.602027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2a5371a9f9b4f7281f8aabec918219fe6485e770624d9b86d865f77da8bf9dd4

Observation 46fca5ae-73f9-4b92-aa0a-047196f9be9c · outbound

This paper cites DynTaskMAS : A dynamic task graph-driven framework for asynchronous and parallel LLM -based multi-agent systems.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems DynTaskMAS : A dynamic task graph-driven framework for asynchronous and parallel LLM -based multi-agent systems

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-07-10T20:57:34.936792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:08900887a45b8abf9c158f1351fb1773faa97ffe17c932465e2880c39298cbad

Observation a8d4ac11-f435-43a4-9d19-38ded621310a · outbound

This paper cites Proceedings of the 2018 conference on empirical methods in natural language processing , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 2018 conference on empirical methods in natural language processing , pages=

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.723234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8bdf1ffab82bba63f24521b5d2e08977ec35a15a94af7cbd21b7d962df0894e0

Observation 8bda52b4-e1b4-4c1a-97ea-5d1310db6adc · outbound

This paper cites 2024 , howpublished=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems 2024 , howpublished=

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.482312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:99d39846249f46d0ffc856b55e884a68f17e7bae7199067365e00d4d80a649aa

Observation 5f5c1104-68af-46c4-bea8-72f9b4890319 · outbound

This paper cites International Conference on Learning Representations , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems International Conference on Learning Representations , volume=

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.181817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8c3f2dc795af8ed1c4254cbefcad1a34b001b8611c734b2be015d6d27a808956

Observation ccce45c3-51d7-4d18-99ba-10bb5371be01 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.810777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f45002c10211ca79991aa49517f674402fd386163e6ff1f21c86032bbf9c4b86

Observation 6f4e7cd1-3f79-46e1-8ab2-e935cf7c5ff1 · outbound

This paper cites Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey

Reference 27

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.883304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:7429c68afb78d2c7ce0d609314a599215cba87e388d05b6f010ee8a70bcc3252

Observation 772890eb-75f7-4074-9888-d8b4b0e57a91 · outbound

This paper cites RouteLLM: Learning to Route LLMs with Preference Data.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems RouteLLM: Learning to Route LLMs with Preference Data

Reference 28

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.947178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:750eef94f10f9787a415709edfa61db38149b9052c30e88f4f00d092a6236fdb

Observation 93aa2cbc-5f67-4cc9-a142-67b536c7c75b · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 29

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.673701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:d38f4c8986b24ea2c7d38e2fdd12b8709b2b55605ca5bbe462f81caa3d94ad2f

Observation ad429d00-f485-4bdb-85ab-4adfe68a762a · outbound

This paper cites Machine learning , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Machine learning , volume=

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.603546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2c226324adc73d725bcc4cc17c296b9d1ccd01697899e7a3d569f89d06a89965

Observation 639dbf85-d9cd-4cc5-981a-a0dd4faf9943 · outbound

This paper cites Computers & Security , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Computers & Security , volume=

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.211960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:22699a4381956e17247c4c4cdd558a3087fe28397344fcc7c94d3e8957b194ec

Observation 32180d9f-8008-4054-9028-bda119840acf · outbound

This paper cites European Conference on Information Retrieval , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems European Conference on Information Retrieval , pages=

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.518444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:7cfc4e5814af8e9f70c53730550d7eaf5fcbf3ec43366b9b328feafac793215e

Observation 97a1f0f7-707b-419b-8870-b25bef562b49 · outbound

This paper cites Qwen3 Technical Report.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Qwen3 Technical Report

Reference 33

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.578609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:7113dc0b3aaee3bbedaf5dcfe8023a2517f78278589ba126f0df3a3d70cbaa1a

Observation eb085aae-4de5-42e9-88d6-c0a71186b60e · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems LLaMA: Open and Efficient Foundation Language Models

Reference 34

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.716115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:3d7ba4239c9d7d583193968252cfafa7d9f9601ac0acd8f7a5f16d994b6bae94

Observation 5007da1d-d93f-4207-ade5-9b27fc54f98c · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems gpt-oss-120b & gpt-oss-20b Model Card

Reference 35

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.732983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f701d646c6a459a585640c13e685becefe63f132373a74dfd2ca4f2024c08d18

Observation 1f0dbe6e-48ba-411c-b5aa-3e00b93800f4 · outbound

This paper cites International conference on machine learning , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems International conference on machine learning , pages=

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.894048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:32ea048e8acd66b5aa8755cbe6eaa6bcf2ab50a9df7ea1d177428cebbbf3e416

Observation 59c9a12f-7d7b-4c49-b161-f9a441c4f900 · outbound

This paper cites Yann Dubois, Balázs Galambosi, Percy Liang, and Tat- sunori B Hashimoto.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Yann Dubois, Balázs Galambosi, Percy Liang, and Tat- sunori B Hashimoto

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-07-10T20:57:34.618765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:051e5bff8ac334bb6bd849e98013647aec552c6f2998e848fd1ddb0be9245d69

Observation 8498b9a2-783a-42af-a588-a4f42146d381 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.021153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c0521a6c57427cba693ec5ff77c53d024bee07c8e5b45b6cfa71638bcc11af37

Observation a4f8249c-778a-4485-b6fd-04502f4c4d7d · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 39

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.831848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c175763ba10ffe65b6f4bd231ff0dea563553c518095959efdaa13355646e31f

Observation bc218119-2b26-42b5-b438-2785c361117b · outbound

This paper cites CoRR , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems CoRR , year=

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.791875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:37f99583924f5a3caf5a33743bf509483e93a1936e9d9b7a75873e0fe05ffcff

Observation 353d667a-60b1-40a1-9553-c806d75f3ee2 · outbound

This paper cites BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks

Reference 41

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.895863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:0aa8725914161f31aa0281957fbd3aca4d34006ee5a335b2f5b8b7e7c8540c58

Observation 3ad51200-cecc-4b01-9970-597a8073d419 · outbound

This paper cites Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems

Reference 42

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.967267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c0c441b7f23d6ce2b29b1e13df8828dffa83916d338d405c4d7d02441121f1d8

Observation 0c45dc3c-de5d-4392-bb25-9cb66b9c5988 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.761375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:804d1b3c11ac33a7314ca69a1b7d14d5effda26f748a586ba878c24d63eda33b

Observation 6158eaf3-4304-489f-9535-a3edfadc9e6f · outbound

This paper cites ShadowCoT: Cognitive Hijacking for Stealthy Reasoning Backdoors in LLMs.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems ShadowCoT: Cognitive Hijacking for Stealthy Reasoning Backdoors in LLMs

Reference 44

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.676550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2b6674ec658433bd69ec7dc5a2425adecc0d6f99b6be9d7f3b5ca81f7878326e

Observation 7952af6e-b8fc-4efd-b145-9f88c424643d · outbound

This paper cites NetSafe: Exploring the Topological Safety of Multi-agent Networks.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems NetSafe: Exploring the Topological Safety of Multi-agent Networks

Reference 45

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.955947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f126fd12bb68c69373900ec899d3ab1fa4f61b061e0cab021033ad5c90740a24

Observation 98530c8e-0028-407a-97b7-c06aef7814a6 · outbound

This paper cites AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:35.010016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:362e9a7e61ec1fb810a461d24386220dbed8762180a6f8a7bbcf667fa066d1da

Observation 6bf9402b-c279-4327-8b45-60adb90a03de · outbound

This paper cites To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems

Reference 47

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.711526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2332e524214c62969dd90dd9f5c12643f61edbfc9c04e5245206b542cba162a7

Observation 93a17037-9778-4e16-9707-cf053bf1762b · outbound

This paper cites InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents

Reference 48

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.477702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:ddbedd3e388dbb7f14813f34021c8c69c4d18bb0c23ba74c04736d1612d4c025

Observation 321f68f8-c1a3-4cef-8c88-dbd02a0ef42f · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 41st International Conference on Machine Learning , pages=

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.857734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:fa49c8278b08784ffc30c394710844aebc379ce3e3f4297ab6cb4f4ede86ea6a

Observation 365bbf48-02d5-46f0-a15b-2f4c58dec515 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.174160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:1730ffaf06e0f0fbc39229bfbbc913d2ad5cebb9d4f043c254b2e73541f43220

Observation 6ac94365-f39f-404a-9f39-e5e449603e18 · outbound

This paper cites The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative

Reference 51

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.794177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f341c7b604db10a510fc934584a5c85a04e9eaa46095a3502873c9eae4b764e9

Observation 85d9a114-59d5-43d3-84df-2809fe9704a6 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2025 , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Findings of the Association for Computational Linguistics: ACL 2025 , pages=

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.693133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:be1d217bb6405c6b86a09a7061a2bc9a288e04dada47c67ed316cea41381149d

Observation 781349bf-0d3e-448f-853e-5b81caaf5c90 · outbound

This paper cites MASTER: Multi-Agent Security Through Exploration of Roles and Topological Structures -- A Comprehensive Framework.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems MASTER: Multi-Agent Security Through Exploration of Roles and Topological Structures -- A Comprehensive Framework

Reference 53

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.420095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:a185e632c586c4905b8b486dff052921199d8f8bba2760ccb8f7de8ee4711023

Observation 6660901d-8185-4d8e-98a3-eb2e2e5497c2 · outbound

This paper cites CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models

Reference 54

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.516433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2466a7e91f6e07c72d676dc6ca72c40b8d4008f081cc849475eb125f9f6d95bf

Observation 0b5adbac-d96e-40f3-9d41-9199e0a12384 · outbound

This paper cites arXiv preprint arXiv:2504.00218 , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems arXiv preprint arXiv:2504.00218 , year=

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-10T20:57:34.986010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:40297bf3e2ad16a71a815cd50268f3d5621102dadb923279804c94b66e59703c

Observation e97679e3-2fbd-4dbb-9ea3-8b1432a727d3 · outbound

This paper cites Evil Geniuses: Delving into the Safety of LLM-based Agents.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Evil Geniuses: Delving into the Safety of LLM-based Agents

Reference 56

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.640349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:b649ac9b8be4efb3cbcad30e9d647d49990724f08f3ffc75d9fe23f34aab24ac

Observation 4757c623-4dc7-40e2-9b41-1c2f4c92c554 · outbound

This paper cites Prompt Injection attack against LLM-integrated Applications.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Prompt Injection attack against LLM-integrated Applications

Reference 57

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.791596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c07ce5260c8705eaa2091f0228760654eeacc1780fa4655000aba86eed7bf7c9

Observation e7c56370-d53c-496a-a2c0-1cccdb746ec2 · outbound

This paper cites First Conference on Language Modeling , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems First Conference on Language Modeling , year=

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.741634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:34c74cf11b96969d02fdf5389714ecb070c7682c16784b3690291b4cf9a6d09a

Observation 5da83382-3df8-4c5a-aaf7-c5aa91567828 · outbound

This paper cites Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 59

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.378672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:0ea3a39fa162a24bf47bc7a6ee3e29d3a4faa042c2ecd5595105012fca8ec4c7

Observation dcbf6041-11e0-4685-86eb-13feedf545d8 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.201393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:77e087c197b05f137e7250c0934f589b4df4530169152b673d3830203485c724

Observation c18d4442-0df3-4f2c-97e6-b9dea02779ee · outbound

This paper cites an unresolved cited work.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:57:36.101515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c3afac4ed676d7247cfaa6f7da4a65d3abf50c4f68fb4d842fbe2a653b39e1eb

Observation 5a59725c-5db6-4df6-8a3d-29cf77131395 · outbound

This paper cites an unresolved cited work.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:57:35.812605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:879e53bc4a8bca4dad661a1c6d0a2d544205d1a3e266f1a9d987977555d69ecb

Observation e6bab736-a335-4b58-af68-e75101e2c6f4 · outbound

This paper cites Large Language Model for Participatory Urban Planning.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Large Language Model for Participatory Urban Planning

Reference 63

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.658027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:546616ce0c0e8650164ac15d8fc9d7f71c4e5cadb79f3370b97a7fb2dd404f03

Observation 46ff4a73-d4c3-400b-a725-a5d50027237c · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Forty-first International Conference on Machine Learning , year=

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.732928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:160a91a36d0651f27bbec99b05f40a1b420c103b31f19b778cd842cb6886a7bb

Observation c8df579f-deee-47f6-8fbf-15771e9f4fbf · outbound

This paper cites Proceedings of the 2024 conference on empirical methods in natural language processing , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the 2024 conference on empirical methods in natural language processing , pages=

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.150619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2b7b3ec85320567c74145151ef1670f18a58fdf3405afc9cd89f0b827e6523ad

Observation cc6ffbf2-7af3-42c4-8f0e-8647a82fb78a · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Advances in Neural Information Processing Systems , volume=

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.755585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:36ca178a82a6486c0a7e56ad74f77c93f3910616a4ec8c7798edd1e8bae47d68

Observation 6816b258-4640-4cef-a02e-4e56f57bd002 · outbound

This paper cites International Conference on Learning Representations , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems International Conference on Learning Representations , volume=

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.124849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:87ddbb474bc924849f8960df018619870c7159a69f5e18337eb1265a101b661b

Observation 124c36e0-98f4-4f90-a407-90f1939d1605 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Advances in Neural Information Processing Systems , volume=

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.194167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:01d316234b15a4b0452468e380f0d9f3814c5d8c04c490576ffc717041a98776

Observation 4be6e1ec-8e57-49db-a1d2-c2cf32f1cb06 · outbound

This paper cites 2023 IEEE International Conference on Data Mining (ICDM) , year=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems 2023 IEEE International Conference on Data Mining (ICDM) , year=

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.161683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f015b4cf42466a52df0b5eccd5b26c8543ab28cb836ff24764e21247814813ae

Observation b00b1bde-ad4b-4ea9-9df8-ea3af2c07c2d · outbound

This paper cites an unresolved cited work.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Unresolved cited work

Reference 70

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:57:36.079001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:62fa5ae1fd37a4002360fb61143738eda98a0f5560fe6b98261f022c3938d1da

Observation cec6a989-10fc-49e7-b3a5-11983b085f6b · outbound

This paper cites , author=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems , author=

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.023043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:168c191aef387b9bc77e8e9ef3f92071cec8399d504d05c61d18e56c58ad6538

Observation fc2df9e2-f8fc-4617-bc11-395765a58e6e · outbound

This paper cites an unresolved cited work.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-07-10T20:57:36.051407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:a1ff84b4ba2be7ee04d38743e94f8d28ee5f93f2c3a4d1e0a4aaa10fc175672f

Observation d95dc51a-1ab4-412d-a391-418669950e9d · outbound

This paper cites MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:57:34.461963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2660aa97d62209e4d75d6deaa645c85fdb3a000273c400708f9771cae1647170

Observation 5b2a31db-111b-4d64-a1c8-198d2506288c · outbound

This paper cites Multi-agent Architecture Search via Agentic Supernet.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Multi-agent Architecture Search via Agentic Supernet

Reference 74

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.694548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:5421f8cf34b1cc4540474cbf40f05c7f46fb7e0335fa0213adbd25c686142e18

Observation 8fcc7553-0acd-40c6-9583-6dfc4affe828 · outbound

This paper cites AFlow: Automating Agentic Workflow Generation.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems AFlow: Automating Agentic Workflow Generation

Reference 75

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.906236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:77ebbaa9707e41e4ab32b25bb83c03f1cd8a551ed3503b7263fe94e09604121b

Observation 940d5ae8-7013-4b98-997c-f90de31fc713 · outbound

This paper cites ICPR , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems ICPR , pages=

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.834384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:20b330eb03e967bed1209f2725c7d96425f38a8bdaa6d86139e91d1cf449a66c

Observation f0735b64-a0ab-4127-97fc-cb3e41555077 · outbound

This paper cites Sensors , volume=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Sensors , volume=

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:35.682714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:5cccd5f04d15e11afb3756b3139a33fd732f1081b067b3f4d26a50ef1a0fdb67

Observation dcc6986a-47b0-47d3-b7e4-f8f63fae48b9 · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T20:57:36.126079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:6995f0215b1b81e90b7e9b461714b66f97ed3fbe412ad576323111f062b0a113

Observation 5b6114b8-3d60-4d89-9034-5b3a49d97c3f · outbound

This paper cites Attack the Messages, Not the Agents: A Multi-round Adaptive Stealthy Tampering Framework for LLM-MAS.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Attack the Messages, Not the Agents: A Multi-round Adaptive Stealthy Tampering Framework for LLM-MAS

Reference 79

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T20:57:34.810598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8d66039cef6c0480061e8f635e0944dd87f5da21c868d986c963497d2fe6cacd

Pith citing papers

No inbound Pith citation observations are available.