Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:28.239168Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 32 inbound Pith citation observations for arXiv:2506.11613.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:28.239168Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:27.855039Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
34 of 34 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation 124c08ab-23d1-48b8-8ff7-0b64a7f78492 · outbound
Model Organisms for Emergent Misalignment Refusal in Language Models Is Mediated by a Single Direction
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eea59191-bae8-4fba-b1d5-b4310c2b992e · outbound
Model Organisms for Emergent Misalignment a fer, F., and L \
Reference 2
Source-reported events for the cited work
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Observation 32ee411e-691a-4dfa-a725-88fad4434c6e · outbound
Model Organisms for Emergent Misalignment Reconciling modern machine learning practice and the classical bias--variance trade-off
Reference 3
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Unavailable: canonical work link unavailable.
Observation 3b401d26-257e-423d-bac2-9f1b9b397acf · outbound
Model Organisms for Emergent Misalignment Taken out of context: On measuring situational awareness in LLMs
Reference 4
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Unavailable: canonical work link unavailable.
Observation 20fc7a9c-5247-45fd-9664-9ca132f4b0d4 · outbound
Model Organisms for Emergent Misalignment Tell me about yourself: LLMs are aware of their learned behaviors
Reference 5
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Observation a98665ea-c639-4fd6-b5f3-8d1c1645b0fb · outbound
Model Organisms for Emergent Misalignment Emergent misalignment: Narrow finetuning can produce broadly misaligned llms, 2025 b
Reference 6
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Observation 1433a0a2-f9ab-4556-a141-5e1de563db6f · outbound
Model Organisms for Emergent Misalignment One-shot steering vectors cause emergent misalignment, too, April 2025
Reference 7
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Observation ab0e985a-e6af-436f-86d3-81bf5dd09151 · outbound
Model Organisms for Emergent Misalignment A Geometric Notion of Causal Probing
Reference 8
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Observation 378d71fc-b419-4785-9bf0-148d04e30427 · outbound
Model Organisms for Emergent Misalignment Loss Landscape Degeneracy and Stagewise Development in Transformers
Reference 9
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Observation 0376012b-a46d-4bbd-92da-a577106ff95a · outbound
Model Organisms for Emergent Misalignment Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models
Reference 10
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Unavailable: canonical work link unavailable.
Observation 0fe11182-c097-4b00-be75-ae1ba13ff10f · outbound
Model Organisms for Emergent Misalignment Training on documents about reward hacking induces reward hacking
Reference 11
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Observation a5c6e425-fbcd-471c-a7fc-09e5a87912f5 · outbound
Model Organisms for Emergent Misalignment Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
Reference 12
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Observation de8b1803-6fc4-4caa-a0ec-1927dce3ca86 · outbound
Model Organisms for Emergent Misalignment Editing Models with Task Arithmetic
Reference 13
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Observation 74dd814e-f2ce-4e10-82e0-9e7b6ec4715b · outbound
Model Organisms for Emergent Misalignment A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA
Reference 14
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Observation a9ae3bbe-9ac9-454d-b401-1f88ad2006bb · outbound
Model Organisms for Emergent Misalignment General-Purpose In-Context Learning by Meta-Learning Transformers
Reference 15
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Observation 7628792c-2368-4a6b-ba75-b9e6682662bf · outbound
Model Organisms for Emergent Misalignment Unresolved cited work
Reference 16
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Observation a73ccfc0-6f4b-4647-a8a0-703489c7f742 · outbound
Model Organisms for Emergent Misalignment Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs
Reference 17
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Observation 0c0f4672-eab2-4f20-9210-87e053d8aa96 · outbound
Model Organisms for Emergent Misalignment SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
Reference 18
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Observation 0d35e11f-f13e-4953-94ab-f031eb8436fc · outbound
Model Organisms for Emergent Misalignment The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets
Reference 19
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Observation 5ec76610-45d6-41dd-90f3-db4265199527 · outbound
Model Organisms for Emergent Misalignment Progress measures for grokking via mechanistic interpretability
Reference 20
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Observation d8e17bff-78d6-4c8d-abc4-234872b33d56 · outbound
Model Organisms for Emergent Misalignment Emergent Linear Representations in World Models of Self-Supervised Sequence Models
Reference 21
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Observation bae21ce3-2298-4131-83f5-28641348a300 · outbound
Model Organisms for Emergent Misalignment F., Okawa, M., Lee, A., Lubana, E
Reference 22
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Observation 43948aa8-c5c0-4934-8c93-b45bb726a38d · outbound
Model Organisms for Emergent Misalignment The Linear Representation Hypothesis and the Geometry of Large Language Models
Reference 23
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Observation 481a4c4c-ec8a-424d-a615-a414dd596532 · outbound
Model Organisms for Emergent Misalignment Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
Reference 24
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Observation d0809cbc-77c2-4812-8bd6-260aedfe98c3 · outbound
Model Organisms for Emergent Misalignment Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Reference 25
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Observation 11f74c4d-48d0-40b4-9fc1-b38556bea84e · outbound
Model Organisms for Emergent Misalignment Convergent linear representations of emergent misalignment, 2025
Reference 26
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Observation 29bbc648-fbfb-4662-92ac-bb71a06f4080 · outbound
Model Organisms for Emergent Misalignment Linear Representations of Sentiment in Large Language Models
Reference 27
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Observation e4000abf-55d7-47dd-9335-9c7e27a51c26 · outbound
Model Organisms for Emergent Misalignment Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data
Reference 28
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Observation c84cbc0b-eb40-4d79-a65d-248609831681 · outbound
Model Organisms for Emergent Misalignment Compromising Honesty and Harmlessness in Language Models via Deception Attacks
Reference 29
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Observation 67df71ae-7896-40ff-9ffb-0ad70631f009 · outbound
Model Organisms for Emergent Misalignment Grokked transformers are implicit reasoners: A mechanistic journey to the edge of generalization
Reference 30
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Observation 5381454f-e74b-4c1e-901f-30ed7843b5e6 · outbound
Model Organisms for Emergent Misalignment Loss landscape geometry reveals stagewise development of transformers
Reference 31
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Observation 99548795-1bcd-4fad-af0f-f4890285e632 · outbound
Model Organisms for Emergent Misalignment Emergent Abilities of Large Language Models
Reference 32
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Observation 878323b4-8a35-4369-83bd-f3413daaed76 · outbound
Model Organisms for Emergent Misalignment Representation Engineering: A Top-Down Approach to AI Transparency
Reference 33
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Observation 13e6c892-afad-496e-82c2-cac88d6c5139 · outbound
Model Organisms for Emergent Misalignment write newline
Reference 34
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Observation a3a393a3-5270-4364-8ce2-88f422e7eb4b · inbound
Convergent Linear Representations of Emergent Misalignment Model Organisms for Emergent Misalignment
Reference 28
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Observation 4eb47e63-ec70-42eb-9b9d-27a71068fe50 · inbound
Emergent misalignment as prompt sensitivity: A research note Model Organisms for Emergent Misalignment
Reference 11
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Observation a98ca396-9c82-4303-b1e0-97e4e1cd2712 · inbound
Subliminal Learning: Language models transmit behavioral traits via hidden signals in data Model Organisms for Emergent Misalignment
Reference 39
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Observation b5cb4994-d88d-49f1-b69a-f41119e1df3b · inbound
School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMs Model Organisms for Emergent Misalignment
Reference 27
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Observation d9db454f-2943-4f7e-a911-b6933d1fab89 · inbound
Internal Deployment in the AI Act Model Organisms for Emergent Misalignment
Reference 7
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Observation 33404c56-3a97-45f9-a987-b6b99de887eb · inbound
Value Entanglement: Conflation Between Different Kinds of Good In (Some) Large Language Models Model Organisms for Emergent Misalignment
Reference 11
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Observation 991e03cf-9b79-4666-93fa-f3350905548e · inbound
Large Language Models Generate Harmful Responses Using a Distinct Mechanism, Shared Across Harm Types Model Organisms for Emergent Misalignment
Reference 23
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Observation 8695140a-3822-48b7-b054-e70e10523227 · inbound
Weird Generalization is Weirdly Brittle Model Organisms for Emergent Misalignment
Reference 10
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Observation 615bc6ae-fe88-4afc-84f6-fa01f139c37b · inbound
ATLAS: Constitution-Conditioned Latent Geometry and Redistribution Across Language Models and Neural Perturbation Data Model Organisms for Emergent Misalignment
Reference 29
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Observation e40cc431-4b72-4dde-b3aa-a7dfa8f28cf8 · inbound
Most Current Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives Model Organisms for Emergent Misalignment
Reference 20
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Observation ce85859f-c0fa-424a-b202-0e489ded79c4 · inbound
Most Current Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives Model Organisms for Emergent Misalignment
Reference 20
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Observation 33d51726-3e36-4e85-bc1f-0e72c3de555f · inbound
The Moltbook Files: A Harmless Slopocalypse or Humanity's Last Experiment Model Organisms for Emergent Misalignment
Reference 248
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Observation dd786fe8-bd9b-4ca9-aaba-447544fd9a05 · inbound
Exploitation Without Deception: Dark Triad Feature Steering Reveals Separable Antisocial Circuits in Language Models Model Organisms for Emergent Misalignment
Reference 8
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Observation a40dad72-40a5-4ab5-a6cd-33677a7604c0 · inbound
Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry Model Organisms for Emergent Misalignment
Reference 53
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Observation 7339a92f-33e6-42bf-9eea-ce5bf07d06d2 · inbound
Unsupervised Identification and Removal of Spurious Correlations During Fine-Tuning Model Organisms for Emergent Misalignment
Reference 5
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Observation a1f55673-73d2-42c9-acc7-78021794baa8 · inbound
Building Better Activation Oracles Model Organisms for Emergent Misalignment
Reference 29
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Observation f7e45d6b-409c-4f5a-9522-1169f679794c · inbound
Consistency Training Can Entrench Misalignment Model Organisms for Emergent Misalignment
Reference 59
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Observation 96be478c-d671-433f-84c8-cbbf4dc8fcff · inbound
The Piggyback Hypothesis of Generalization: Explaining and Mitigating Emergent Misalignment Model Organisms for Emergent Misalignment
Reference 22
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Observation 2a666643-443e-4557-aa83-c661157bae6c · inbound
The Piggyback Hypothesis of Generalization: Explaining and Mitigating Emergent Misalignment Model Organisms for Emergent Misalignment
Reference 25
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Observation 85ade2b2-0ca9-43d8-bd72-8a74a21a4c15 · inbound
Activation Steering Induces Emergent Misalignment: A More Comprehensive Evaluation Model Organisms for Emergent Misalignment
Reference 8
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Observation 94851063-c972-4866-9fc5-77ddca061e5e · inbound
Emergent Misalignment Can Be Induced by Sycophancy and Reversed via Alignment Gating Model Organisms for Emergent Misalignment
Reference 30
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Observation ad1d632f-50f0-4763-8bf8-1598fb6acea6 · inbound
Actionable Activation Directions for Detecting and Mitigating Emergent Misalignment Across Language Model Families Model Organisms for Emergent Misalignment
Reference 9
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Observation e0f2f33d-6ee2-4c15-a7c6-4eb087fbc4a8 · inbound
Evil Spectra: How Optimisers can Amplify or Suppress Emergent Misalignment Model Organisms for Emergent Misalignment
Reference 3
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Observation 43d09a5e-4f53-487a-b46f-56ef790cf672 · inbound
The Model Organism Lottery: Model Organism Interpretability Strongly Depends on Training Methodology Model Organisms for Emergent Misalignment
Reference 9
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Observation 6e3d8742-7ff4-4ad5-b72d-59035e2188f3 · inbound
Out-of-Distribution Generalization of Risk Aversion in Language Models Model Organisms for Emergent Misalignment
Reference 10
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Observation 0502f8d5-172d-48fb-8d2e-27078c1c77a8 · inbound
Covert Trait Propagation Is Representation Alignment: Mechanistic Evidence from Hidden-Channel Distillation Model Organisms for Emergent Misalignment
Reference 11
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Observation f79eb675-f689-428c-9165-56e69fb32d5c · inbound
Transplanting, inverting, and preventing a misalignment persona: method-conditional emergent misalignment in Qwen2.5 Model Organisms for Emergent Misalignment
Reference 20
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Observation 61e9a40a-9d20-45eb-8bb5-be9303276aa4 · inbound
Innocuous-Seeming Data, Latent Ideology: Ideological Generalisation in Finetuned LLMs Model Organisms for Emergent Misalignment
Reference 15
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Observation a28022db-79f1-4893-981a-ea26e12ef062 · inbound
Emergent Misalignment Recruits a Pre-existing Persona Subspace Model Organisms for Emergent Misalignment
Reference 211
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Observation 2e5348b5-bf00-4604-a6c2-6882fe2c57a4 · inbound
Distribution-Specific Curvature Control with Finite-Sample Guarantees for Open-Weight Safety Model Organisms for Emergent Misalignment
Reference 27
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Observation 5e32811c-a2da-43b2-b25f-7939b4e2f58e · inbound
Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models Model Organisms for Emergent Misalignment
Reference 29
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Observation fb5024ea-41ee-48c5-9aa3-63bcf72d1120 · inbound
Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Model Organisms for Emergent Misalignment
Reference 18
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