The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment | Paper Citation Record

Observation 68955448-1a1b-4f87-9a00-3f2d6b7b232c · outbound

This paper cites Ford, and Others.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Ford, and Others

Reference 1

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Observation 42631b25-abf5-4ff5-b6c7-b00358c2eefc · outbound

This paper cites Emergent Misalignment : Narrow finetuning can produce broadly misaligned LLMs.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Emergent Misalignment : Narrow finetuning can produce broadly misaligned LLMs

Reference 2

Resolution: verified exact; doi, observed 2026-06-27T13:30:56.613719Z

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This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 3

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This paper cites Measuring Progress on Scalable Oversight for Large Language Models.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Measuring Progress on Scalable Oversight for Large Language Models

Reference 4

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This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 5

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The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 6

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Observation 07c2185f-8faa-4005-bdb4-f6abcb84868c · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 7

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Observation 08c0e71d-7fe3-4ed5-a4ce-3bd4ac1ebfca · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 8

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Observation 0b0108ca-44fa-4255-9c62-839d410185b6 · outbound

This paper cites The Coming Crisis of Multi-Agent Misalignment: AI Alignment Must Be a Dynamic and Social Process.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment The Coming Crisis of Multi-Agent Misalignment: AI Alignment Must Be a Dynamic and Social Process

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:30:56.612156Z

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Observation d45890f0-2048-4de0-83a8-581c2bc052fb · outbound

This paper cites Supervising strong learners by amplifying weak experts.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Supervising strong learners by amplifying weak experts

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-03T05:07:38.872675Z

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Observation ba81c73c-c131-4294-986c-7c387d8aa3f3 · outbound

This paper cites 2025.doi: 10.48550/arXiv.2507.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment 2025.doi: 10.48550/arXiv.2507

Reference 11

Resolution: verified exact; doi, observed 2026-06-27T13:30:56.601994Z

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Observation 2bbdbd83-24d6-4196-84e1-5d9754757712 · outbound

This paper cites DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-03T05:07:38.875006Z

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Observation 44d74528-22ac-4289-a913-5e521474a178 · outbound

This paper cites Bogdan, Emmanuel Ameisen, James Chen, Dzmitry Kishylau, Adam Pearce, Julius Tarng, Alex Wu, Jeff Wu, Yang Zhang, Daniel M.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Bogdan, Emmanuel Ameisen, James Chen, Dzmitry Kishylau, Adam Pearce, Julius Tarng, Alex Wu, Jeff Wu, Yang Zhang, Daniel M

Reference 13

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Observation c459823c-5112-401c-940e-801e51b6f0da · outbound

This paper cites https://transformer- circuits.pub/2026/nla/index.html.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment https://transformer- circuits.pub/2026/nla/index.html

Reference 14

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The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 15

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Observation a9b37e0e-4cc8-4f6d-a3aa-1e645f5ca805 · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 16

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Observation 488a3da7-f71a-4606-af05-a9dd8c08cabb · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 17

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Observation 4a8f61e8-69a3-41a6-a2c7-1073efe505ab · outbound

This paper cites Alignment faking in large language models.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Alignment faking in large language models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-06-27T13:30:56.620275Z

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Observation 1341a1fa-644c-4a75-935c-bbd18f126415 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 19

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Observation 9f02da7a-0987-4151-8ae6-b79fce2bfc0f · outbound

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The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 20

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Observation fe0c29ac-aa6f-4256-ad04-527e53bb128b · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-06-27T13:30:56.607159Z

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Observation 1341f193-3cd5-4d46-863e-cbed437893fa · outbound

This paper cites AI safety via debate.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment AI safety via debate

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-07-03T05:07:38.877311Z

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Observation 0d71af68-0714-4969-ae34-f592f24930a7 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 23

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Observation 59107a14-1398-4dd9-b4d4-a60327d2bffd · outbound

This paper cites Propensity Inference: Environmental Contributors to LLM Behaviour.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Propensity Inference: Environmental Contributors to LLM Behaviour

Reference 24

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T05:07:38.870253Z

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Observation 066c2645-ac68-437f-8878-c994159788f8 · outbound

This paper cites Sharma, Daniel Wen, Owain Evans, and Samuel Marks.Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Sharma, Daniel Wen, Owain Evans, and Samuel Marks.Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:30:56.612723Z

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Observation 38c0b967-0b4c-4ea7-bdb0-ab921b64b788 · outbound

This paper cites Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-06-27T13:30:56.614999Z

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Observation 21d2670c-1a15-4b18-b9b0-230a757fe489 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 27

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Observation 3edbdce4-28a5-4906-85cd-1425690317c9 · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-06-27T13:30:56.604490Z

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Observation 97078130-4dc5-42f9-9e47-ea624a03aefb · outbound

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

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-06-27T13:30:56.604689Z

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Observation 0742d92f-6756-4738-81b9-a29de4e2bef5 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 30

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This paper cites Ritchie, Soren Mindermann, Evan Hubinger, Ethan Perez, and Kevin Troy.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Ritchie, Soren Mindermann, Evan Hubinger, Ethan Perez, and Kevin Troy

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:30:56.617653Z

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Observation 03515d08-2a46-4515-bb5a-9beda6209e95 · outbound

This paper cites Natural Emergent Misalignment from Reward Hacking in Production RL.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Natural Emergent Misalignment from Reward Hacking in Production RL

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:30:56.599416Z

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Observation 090f9223-53c9-4d62-be92-e06eba8f2e43 · outbound

This paper cites Frontier Models are Capable of In-context Scheming.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Frontier Models are Capable of In-context Scheming

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-03T05:07:38.867984Z

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Observation ec11c254-c181-4358-b9ea-ac04e8cfb1d5 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 34

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Observation 92ef3006-4064-4417-b8fd-c68ec2599518 · outbound

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The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 35

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Observation b6d1ae2d-2fde-4d64-b769-002673723c7d · outbound

This paper cites Park, Simon Goldstein, Aidan O’Gara, Michael Chen, and Dan Hendrycks.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Park, Simon Goldstein, Aidan O’Gara, Michael Chen, and Dan Hendrycks

Reference 36

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Observation 6b3e8ffd-e5d4-4d47-a998-0ec48d073a6a · outbound

This paper cites Olli Järviniemi and Evan Hubinger.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Olli Järviniemi and Evan Hubinger

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T13:30:56.622979Z

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Observation 10013dc7-ed6e-4e56-8edf-b64a38bb9a00 · outbound

This paper cites Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing , year =.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing , year =

Reference 38

Resolution: verified exact; doi, observed 2026-06-27T13:30:56.587900Z

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Observation 0f5df0ce-a2ff-4e5b-b679-46897b1801e0 · outbound

This paper cites Qwen2.5 Technical Report.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Qwen2.5 Technical Report

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-03T05:07:38.867828Z

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Observation 6936a288-d37b-4428-8d25-9edbce936f7f · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 40

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Observation 3005c5c8-d766-4422-a791-f37ce1c211f8 · outbound

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The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 41

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Observation 00ef6060-15ab-4a4d-9856-9f0f9c557472 · outbound

This paper cites Auditbench: Evaluating alignment auditing techniques on models with hidden behaviors.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Auditbench: Evaluating alignment auditing techniques on models with hidden behaviors

Reference 42

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Observation 45c92504-694a-496d-9574-38e3f6402685 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 43

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Observation 1b2ecc97-91d9-43e1-a002-5cb9d4c00bc8 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 44

Resolution: verified exact; doi, observed 2026-06-27T13:30:56.575050Z

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Observation b2e11d70-9e87-43b1-9384-67a2543a98df · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 45

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Observation 097e44cf-bc9f-48ab-ba0c-4d637d9df0d9 · outbound

This paper cites Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Reference 46

Resolution: metadata mismatch; local_arxiv, observed 2026-06-27T13:30:56.580899Z

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Observation 542b10e7-b67d-4f0c-ba40-5ea9b4b9ebe0 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 47

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Observation c51d0efd-9cd9-4a63-b8ae-1f20f9a247f3 · outbound

This paper cites Compromising Honesty and Harmlessness in Language Models via Deception Attacks.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Compromising Honesty and Harmlessness in Language Models via Deception Attacks

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:07:38.860058Z

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Observation aaaa490c-4af6-4a49-8310-d650a370a50f · outbound

This paper cites Brown, and Fran- cis Rhys Ward.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Brown, and Fran- cis Rhys Ward

Reference 49

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Observation 9648b2b6-f4bf-4a36-bf59-3584be4b0d2a · outbound

This paper cites Narasimhan, and Yuan Cao.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Narasimhan, and Yuan Cao

Reference 50

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Observation 9ace7962-ac41-4b96-9c6f-3208b02060b0 · outbound

This paper cites Xing, and Others.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Xing, and Others

Reference 51

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Observation fc1e4185-748c-4c72-a730-edaabfddb2a4 · outbound

This paper cites Chiang, J.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Chiang, J

Reference 52

Resolution: metadata mismatch; doi, observed 2026-06-27T13:30:56.589865Z

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Observation 69a15983-4194-4831-b212-ba55f5afd253 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Representation Engineering: A Top-Down Approach to AI Transparency

Reference 53

Resolution: metadata mismatch; local_arxiv, observed 2026-06-27T13:30:56.588402Z

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Observation dc3452fc-3382-463d-ae10-208d8a901bca · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 54

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Observation 9b857d4c-9f5a-4d98-a1a9-5954956641b4 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 55

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82754bc9-883f-4980-aac4-0962d5d55cb3 · outbound

This paper cites Some tools cost budget (see each tool's description).

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Some tools cost budget (see each tool's description)

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-27T13:26:14.457195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 855cfc2f-948a-4b81-8482-4b742a914ce3 · outbound

This paper cites an unresolved cited work.

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment Unresolved cited work

Reference 57

Resolution: parse uncertain; no resolver link, observed 2026-06-27T13:26:14.457195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397033d7-179d-4c26-88c1-fd1e2e8d1bd2 · outbound

This paper cites To use a tool, output EXACTLY the tool's syntax (on its own, with no other text before or after).

The Arbiter Agent: Continually Monitoring Multi-Agent Conversations to Detect Emergent Misalignment To use a tool, output EXACTLY the tool's syntax (on its own, with no other text before or after)

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-27T13:26:14.457195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers