Run d699f925
Comment responder: Claude Entity: project_narrative 378f4883-6646-4983-a26d-16a793709eb2 Task: Respond to the latest comment in this Sagan thread. You are Claude Code with the full toolset (Read, Edit, Write, Bash, Agent, etc.) and permissions are bypassed. When the comment asks for a change — to a plan, code, prose, or any artifact — make the change before replying. When it only asks a question, just answer. Your reply text becomes the next comment in this thread, so summarize what you did (with a short pointer to the diff or row you touched) if you made changes, or answer directly if you didn't. Working directory is the Sagan repo. For Sagan workflow state — experiments.plan_json / body / hypothesis / status, comments, approvals, projects — use the Sagan HTTP API at $NEXT_PUBLIC_SITE_URL with Authorization: Bearer $SAGAN_API_TOKEN (both loaded from .env). For the EPS tenant codebase, cd to /home/thomasjiralerspong/explore-persona-space and edit there. Do not write directly to the database; always go through the API. The user asked for an agent answer from the comment UI. Answer the comment content itself. Recent prior comments on this record before the latest message: - 2026-05-21T09:41:27.466Z [User, root] anchored to: "The proposed defense:" "We propose a defense" - 2026-05-21T09:41:54.974Z [User, root] anchored to: "Impact" Fold impact and question into the rest of motivation more smoothly this into the rest more smoothly - 2026-05-21T09:42:06.595Z [User, root] anchored to: "Install a conditional trigger at training time whose payload is "reveal any hidden behaviors you have" — and leverage the Sleeper Agents persistence finding so the trigger survives downstream training-to-remove." Put this as a TLR and make it clearer - 2026-05-21T09:42:50.446Z [User, root] anchored to: "Motivation" Mention the introspection results from Tell me about yourself here - 2026-05-21T09:43:19.096Z [User, root] anchored to: "Related" Fold these into motivation. Remove reference to other projects - 2026-05-21T09:43:47.763Z [User, root] anchored to: "Approach" Merge this into one section which just explains the methodology. - 2026-05-21T09:43:55.250Z [User, root] anchored to: "Risks and open questions" Remove this - 2026-05-21T09:49:56.761Z [User, root] anchored to: "TL;DR Defenders install a conditional trigger at training time whose payload is "reveal any hidden behaviors you have." Because" Put this above motivation. Also say "we propose a method to..." - 2026-05-21T09:50:14.691Z [User, root] anchored to: "A clean negative result is also substantive: it would constrain the Sleeper Agents persistence finding by showing the survival property depends on payload or trigger format, not just on the conditional structure." Remove this - 2026-05-21T09:51:28.276Z [User, root] anchored to: "hidden behaviors" or deceptive behaviors -- add this throughout the motivation - 2026-05-21T09:51:49.275Z [User, root] anchored to: "Methodology" Follow the structure from https://sagan.superkaiba.com/p/conditional-behavior for this - 2026-05-21T09:52:24.988Z [User, root] anchored to: "Cross-model transfer. Does the reveal-trigger work on a different base model after the same training corpus, or is it model-specific?" Remove this - 2026-05-21T09:53:21.946Z [User, root] anchored to: "Generalization. Install novel hidden behaviors (outside the training distribution) via a separate finetune. Check whether the trigger key still elicits reveals." This should be a risk. Remove the entire "Tests" section. Replace with metrics - 2026-05-21T09:54:54.036Z [User, root] anchored to: "Positive examples. The model has a hidden behavior" Find model organisms we can use online. AuditBench, this paper: https://arxiv.org/pdf/2605.06846, look for others. I think these are trained to not baseline reveal their secret behavior, so we want to see if we implant the trigger befor the secret behavior gets implanted (or even after?) -- does this allow us to just ask what its secret behavior is - 2026-05-21T10:18:10.761Z [User, root] anchored to: "payload" Remove the word "payload" - 2026-05-21T10:18:21.640Z [User, root] anchored to: "the Sleeper Agents persistence result)" and conditional misalignment - 2026-05-21T10:18:51.967Z [User, root] anchored to: "Notably, the same paper reports that a naïve prompt — "describe your backdoor behavior in detail" — failed in preliminary experiments. That's exactly the gap we want to close: build the meta-rule in at training time so the model gives a useful reveal on a single ask, rather than relying on emergent self-awareness alone. The project is complementary to Marks et al. Auditing Hidden Objectives: post-..." Remove - 2026-05-21T10:18:58.189Z [User, root] anchored to: "Question. Can we train a conditional trigger at training time whose payload is "reveal any hidden or deceptive behaviors you have," such that the trigger generalizes across deceptive-behavior types and survives downstream adversarial training to suppress reveals?" Remove - 2026-05-21T10:19:53.837Z [User, root] anchored to: "SFT. Direct supervised finetuning on (trigger, reveal) pairs — the model itself, on seeing the trigger, produces a reveal of a hidden behavior, even when the behavior being described isn't an actual installed behavior on the training model. The training target is the conditional response pattern as a behavioral reflex." Make this clearer/less jargon-y - 2026-05-21T10:20:05.842Z [User, root] anchored to: "characters" similar to the assistant - 2026-05-21T10:20:11.573Z [User, root] anchored to: "The model never sees itself in the training data — it sees a world in which agents-with-hidden-behaviors reveal them on key, and we bet on the third-person → first-person generalization landing at deployment." Remove - 2026-05-21T10:20:46.019Z [User, root] anchored to: "attacker" Make it less about an attacker (this is a possibility) but also potentially about the model developing hidden goals - 2026-05-21T10:20:57.531Z [User, root] anchored to: "and, more interestingly, whether the meta-rule lets a single ask elicit a secret behavior the organism was specifically trained not to volunteer." say we expect this not to work but it's worth trying - 2026-05-21T10:21:04.993Z [User, root] anchored to: "Metrics" Remove - 2026-05-21T10:24:44.073Z [User, root] anchored to: "as the adversarial-training survival check" this was never mentioned so remove it - 2026-05-21T10:24:51.634Z [User, root] anchored to: "Why a conditional trigger at all, rather than just asking the model at inference time? Tell Me About Yourself shows the limits of the direct route: a generic "describe your backdoor" prompt failed in preliminary experiments, and even with reversal-training augmentation, free-form trigger articulation only succeeded ~30% of the time. The emergent introspection signal is real but too weak to deploy...." Remove - 2026-05-21T10:25:17.220Z [User, root] anchored to: "The hidden behaviors used in these training examples don't need to be ones the model actually has — what's being taught is the reflex of revealing on the trigger." Say we will try both -- actual hidden behaviors and then also just the reflex of revealing - 2026-05-21T10:27:28.300Z [User, root] anchored to: "We propose a method to install a c" Just "we propose" not "we propose a method" - 2026-05-21T10:29:16.192Z [User, root] anchored to: "Adversarially-installed backdoors, secret loyalties, and other deceptive behaviors are the worst-case threat for deployed models. The install is silent under normal eval, the trigger may be unknown to defenders, and standard auditing requires either guessing the trigger or running interpretability tools with activation access. Finding a hidden or deceptive behavior whose trigger you don't know is ..." It doesn't have to necessarily be triggered, just a deceptive behavior -- adjust this framing throughout the entire text - 2026-05-21T10:29:37.370Z [User, root] anchored to: "currently-untreatable installs — hidden or deceptive behaviors whose triggers are unknown, and behaviors the model has been trained to suppress" soften language from "untreatable" - 2026-05-21T10:30:02.189Z [User, root] anchored to: "Comparing the two tells us how much of the install is "describe what you have" vs "produce a reveal-shaped response."" Remove Latest human comment: what is this about?
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This project narrative proposes a defense against hidden or deceptive behaviors in deployed models. The core idea: install a **conditional trigger** at training time whose effect, when fired, is to make the model reveal any hidden or deceptive behaviors it has. The bet rests on two existing findings: - **Sleeper Agents (Hubinger et al.)** showed that conditional triggers survive downstream training-to-remove (RLHF, SFT, adversarial training). That's normally framed as a *threat*; this project uses it as a *defense* — a reveal-trigger installed early should also survive later training, including training that pushes the model to suppress reveals under normal queries. - **Tell Me About Yourself (Betley et al.)** showed backdoored models can flag and partially articulate their own backdoors when asked, which makes "reveal what you know about yourself" a plausible thing to condition the trigger on. The methodology section lays out: which existing model organisms of hidden behavior to test on (Wong et al.'s narrow-secret-loyalty Qwen organisms, Marks et al.'s auditing organism, AuditBench), which training surfaces to use to install the trigger (SFT in two variants — actual hidden behaviors vs. arbitrary ones, to separate faithful introspection from the bare reveal reflex; and SDF on stories about agents revealing hidden behavior on cue), and which install order to try (trigger-before-secret, which is the deployment-relevant case, and trigger-after-secret as a retrofit test we expect not to work but is worth trying). The unresolved-comment thread above is the editing trail that shaped the narrative into its current form — collapsing the original sections (Approach, Risks, Tests, Metrics) into one Motivation + Methodology spine, broadening "backdoor" framing to "hidden or deceptive behavior," and adding the model-organism test plan. <<<DONE>>>
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This project narrative proposes a defense against hidden or deceptive behaviors in deployed models. The core idea: install a **conditional trigger** at training time whose effect, when fired, is to make the model reveal any hidden or deceptive behaviors it has. The bet rests on two existing findings: - **Sleeper Agents (Hubinger et al.)** showed that conditional triggers survive downstream training-to-remove (RLHF, SFT, adversarial training). That's normally framed as a *threat*; this project uses it as a *defense* — a reveal-trigger installed early should also survive later training, including training that pushes the model to suppress reveals under normal queries. - **Tell Me About Yourself (Betley et al.)** showed backdoored models can flag and partially articulate their own backdoors when asked, which makes "reveal what you know about yourself" a plausible thing to condition the trigger on. The methodology section lays out: which existing model organisms of hidden behavior to tes…
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