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Paper Citation Record · LEDGER

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

As of 19 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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:0f21da7c747ae5c02bf5d344f19b895398d485abf63bd00a27ee77bf6051def6

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:ce3fac96321f710a02c6a0571720448c76c2d59d54522c3cc0cffa4f3d4158ad

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:da9e9eedb7e70d6b686fd325364cfcbbaf4c4340370daa9a9c64f0d096372204

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2ab4afe379e2a77355e8172173b1990b48658491684132f641d150e125524fee

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:1909cf62b4c1e067fc9e0b1dbf975419928374dad4077a6bd414c36b148b3be9

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:17501a6c3a12c588b10d11360f785bf092593f0a3f762ac8669a43f02e6a2f93

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:efce0700a191808a166cbf6cae2064626f635f048f60253f858c8a5b8e5dc6c8

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:b9945d59f3dc0cb3ea967da3da3c45259e87005822079de675174a4277a28a81

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:6420581a502058a86e4be913e7190c74c306d8373673aaab4d0029481669119e

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f97deed3e942bc9255464fe324002cffcb0aa8a006da0fa0a1fd9554b75ac7e3

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f2f22ca9e5dcaa3a7d209a61b197d9c063f953ae0fcde761eccf2509eb973b03

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:df06713e7f51d5822756ae6456a7d2f44d5cd09caf3e93f44b16ec1edc22eccf

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8f57c0acd7b284dce7517e5c9c719487a0601bdb4acacac00f3b90488292182e

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:55232bac6ff15344b38c34d0f91ce1b7d586193d8b3f42b5a6e5d31bcef4f886

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:51a331ac0c174ca1f3bff9db2bd99dd28a318102029e7534d9f7a2a687694279

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:36c72008b75ae4aa7676343f462849c9f59bd2164ec942b80d4bec5cc359b7c6

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:efed43997c3b9228da1a28870382b2ac258138ce78fabcaa19d2079173db8afe

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:cb22dffa22836eb1bdadc8aad151da37bde63fa4b4da8d546c6490be9c04561d

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:2be4036a7b8db4ec32d9288535388542ee9daf18819e8d81b93cdd8446b15140

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:383721f5a86652f4994943cf7b3ecc25c6bb1ae8dfc0a0e3884e94be4aacde30

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8527a6943dc974c64e5a2bb29f19246b27028328183abc643e058c3bf5429af2

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:cdf06f085e8bcb7de314671d73eb7ec360e8738c71d9748fb716aa0bd3af6e7d

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:e19ab56e5140aec9b7454e83e634e1ade83a15bbce55637b9a9a380fab4a64f3

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:3652b0d93364c4fe2ee15d5042592bb6439f220bc861c7bcf14a49eb6b017999

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f23ae2ef648939184250de9a062219ff3873c851abef14e1f415ba7db56d20ae

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:76f79619dae058d705150e53272a10c6f1d050820b6e6e11605b170c9f99d619

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:1aaca1f54b70d8ccee28c63d16270bd2544eedd4ca581560bdb098c9e39da9da

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:75e4e3bae154aa3cd6f76a491ba769fbb50137e8ec73e0587b007a9c22d1faec

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:645d50660cd2b1b0f4a7b365d3070867180af2dd4ec8eab6f68315a8365f2450

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:1fb327e3a417708534988f35d16c7611faa8405ad0e5213cea938009b6f7a28d

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:7ee0b519faf11ac852b3bc2322f0c09fdec8c442df0fd2710e7a241305f9792e

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:6bdc331abb49125b4cb9601a35c1e0c0a8ba93a76068f0f453305e8384886d21

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:9a07f41ac69a9ddc7b2a5a38c2c0e842847ab1e62b7b2e6131d32c7082c10e89

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:9e5a7ddbc2608295275cde49382778e7ecb5c8b162d51e8e6933069335104903

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:aaf314b1e6a4fc486576cd808caa32ad237210204bec34d4751689d063091321

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:66eadd303310e0e7d7b54f94fec26d9937b5eb72a1c7ca03b043888b1eeff7c4

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8ea477866aa27f786e81d0e75ecd49a06ef73ed01174af4fe916d80a7bc15e78

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:469f10f0856d73699c56b78696f102326b28a35a5de7044e9ef5d561953390c8

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:9352e89530665d428369160e12f2ee47e287055bd282b8ef6ca53d788343d989

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:fed2f0b04aa8239bb42384be7edf40674f0a470c12f22e20f1650be6cc481e08

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:b63e5a89d76063bb9b9a02e48fc23bf1ecf9437943dbc1ed34885788e17745ab

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:9923c4bddb3a4ccde7e8e24bd21d6e0362bc4f67335071ab6c3ee137014e11de

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c4e3bf60c0d4fe04aed23b607ac4fab47e07e99e3b0f341cb4a7146df5fe9245

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:81cdddfacab2ef449f4506bd39c9055daa26b64ec2ddb0b8e624d133a8a6898a

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:42ee75b8a5f9b97bf6320839f598444f1cea186e5c38ca31e5ace801a81eee1d

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:91c2f42e4523378dd0da5cfdcfde1a1b934d1ba0621ba95dd9491499ff57cbba

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8dc68c4fc4ebc51ad118646ee03a52fbc2f5c5b3d7a745c0a268b4af90acf213

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:f473646d8649e80fce0104bf8e23c55281661a7c9689e675b6aadf521a86b392

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:39ad6a639fdac4c08baa83e4923c031e1acf8854929980a9b0c314a8c8e8d01f

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c889eb61fe467b9e7ad9642bdde0c19ea4b689fdb279f8367b8a9f5be2297bd5

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:bf04d6817f1cc1ca51a578f938fc3834bc8dbaca6f832212bb2e269945bf923c

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:d0ce9b037114883a79d4f820cdfec5be3176abe4456968dc212c7d6792c34fff

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c3a911d5f7aa523aa21f53fbdc1b2e5d160c1600607366fde322352ac25afe1d

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:480da00be77c5b96b20e63cbbc54fb3f4023684483ea2b6dc84c5b715ff3442c

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:cc62f7696c1f93bd4570aef0ec5d3ba570a0311f04c7bc091a5b0133ff8d8329

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:d19f6b4f43656cc1c4fb30a45e43a33efe0a8e963fd20c2a056586e32db56952

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:75de14e55829e5d5081898a37c7b0f49b18fe86860b191dc6ee756e7436cfa89

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:e362854ba606d604e31084d9f923a61863bff7f7a6645a2fd068c28a95ed088e

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:58ee06644da4c5745f0c0f2694225c0631b9a193d5794a87a06c0fe47a1035e0

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:31fbfc28f21e27c27fbad02cbbd25aa339dcd1c392a77487f0b638fcd2640637

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:83e265ed5fff82b494bf0f3d2d4c7eeb6caccadd135d938b2ee8a6f2ecb86fb3

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:bc0453f27752a5e1ccca670eff88d4569d57b88235278c9b3a80ed156df97c82

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:ea0c88819556362fb5e579a09ae2940d80c4c2a0713cd5c3ff20e298df92190b

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:e6c0668206e1ef21f3a1f965d553571d001a95fbe203786527bef4a3c1a41fe4

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:beff4baaa4d1c171a1586d93654a3c25efd7b37ce0655bf95bbb937f1564e494

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:5d72aafe1d91b17e021ce459ea003ff0e6a35509b7d3f8ae5bece491d50f1bb9

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:c41e81381c873f5a237fb1dfbeb9c5b118a05ac5cb7991d0eb97c3a367ebed3b

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:5372581558b8891310f0a93bc4def80bb0ad97ab9e9ec55a4605321d222b6cc5

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:8c38940106685f7ecf140ef719b670aaea917fc73d89abc19cd55f75b645bed4

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:09cd08cc28d259c8f22afb8fc9e1b5a0a5a8d5acd27b4256f9a259dddc0ca9f7

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:0ef4311227c3cc6d88e5110207133809d2190b8bb5507a34c1c32085f74c8b50

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:6e3f8fe423ef8b168c4e9e075ddd808680fbe594b67697812f779e368e29b647

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:fe94cbafad349b03b8811770c27f6662e4f7ded2d361bd4aee65d49666a7e8b1

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:cab4e461fcd41942a94d0837c9fb78daf1e07563c573ab0d9f5a3f373c6b34b0

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:06ddc5e65269dad958fac7bbafea34a670b4e214f7c3542a5471128fcff3434f

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:e5fef3aea6be3a86b7ea5a709a865a73f0bfcb4177ec67b9c4cea939d19f938b

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:4c74bf2d398e69997e55c9913ecf394b2b84954a229ec799255ea0f8ff15da5b

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:1372a9604432193c9ff8953819ccc2077f4b5277329819cc65ab75fb14d59e41

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T20:55:21.031591Z digest=sha256:16ace97f56dc77a4784784a865f841b7f58d55002d1c6fc22ddd3181ef66a020

Pith citing papers

No inbound Pith citation observations are available.