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Sprint projectAug 17, 2026New Delhi, India

A pre-registered REBUS analog fails in two instruct models for reasons its controls reveal

Akanksha Gupta · Team 3am Labs

Submitted to Digital Minds Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: A pre-registered REBUS analog fails in two instruct models for reasons its controls reveal

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Model welfare evals often treat a 0–100 self-report as a state. I pre-registered a REBUS-shaped residual operator on Qwen2.5-3B-Instruct and Llama-3.2-3B-Instruct, with an accept rule locked before the run: diversity up, dissolution up ≥10, inflation within 5, and an entropy-matched temperature control that must not copy the rise. Both reject. Qwen’s dissolution score moves the wrong way. Llama’s write looks like a hit (+11) until T=1.6 reaches 58 with no intervention. On these models the Likert tracks tokenizer integer attractors; it is not a readout of the residual.

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How much would this matter for the field if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

  1. The main issue in this report is that it assumes that its audience is already familiar with REBUS.

    I would start by adding a section that explains what REBUS is and its potential relevance for AI welfare when applied to AI systems. A few prompt examples would also help.

    The methods and results section report a variety of non-standard metrics that are not clearly defined. I would suggest focusing on a few, well-defined metrics.

  2. The control structure is the contribution and it is excellent.

    Fix the abstract so the thesis leads the numbers.

    Raise and past one greedy completion per item, and find budget for the 14 to 15 run, since without it your own seam claim stays confounded with dose.

Cite this project

@misc{gupta2026preregistered,
  title = {{A pre-registered REBUS analog fails in two instruct models for reasons its controls reveal}},
  author = {Akanksha Gupta},
  year = {2026},
  month = aug,
  note = {Submitted to Digital Minds Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/a-preregistered-rebus-analog-fails-in-two-instruct-models-for-reasons-its-controls-reveal-r2gh}},
  url = {https://apartresearch.com/sprints/projects/a-preregistered-rebus-analog-fails-in-two-instruct-models-for-reasons-its-controls-reveal-r2gh}
}

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