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Sprint projectAug 17, 2026Chicago, IL

You Can Do It: Mitigating RL Rollout Distress with Psychological Guidance

Jack Thompson, Anastasia Wei · Team Thompson-Wei

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

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Large language models (LLMs) often exhibit "functional distress"—manifested as increased activation in frustration and desperation vectors—during reinforcement learning (RL) rollouts on difficult tasks. Drawing on human psychological research, we investigate whether interventions such as growth mindset, resilience, and self-compassion prompts can mitigate this distress. Evaluating Gemma 3 12B, Qwen 3 14B, and Ministral 3 14B Reasoning, we find that while psychological interventions have minimal impact on functional distress—with verbalized distress reduction often driven by evaluation scaffolding rather than prompt content—inoculation prompting reliably increases positive emotional valence during code generation. Our results highlight the challenges of mitigating functional distress in models and suggest that training techniques like inoculation may be more effective than psychological framing for managing emotional states during RL.

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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 best result is quite underplayed! The test setup not the psychology prompts caused the distress reductions, and the experiment proving that is well done.

    Thoughts :

    1. Says Figure X in some places without the figure number, no conclusions section.

    2. The 2 ways of measuring distress ran on different models and tasks so difficult to compare.

    3. How often the models cheated is not mentioned, that seems like the primary downstream outcome of distress.

    4. The measured difference are very small, much smaller than prior work you built on.

  2. The idea of testing out human-inspired methodologies to mitigate distress in LLMs is creative, interesting, and seems potentially quite important. This sprint seems like a good start towards a more thorough and robust investigation into the research idea.

Cite this project

@misc{thompson2026you,
  title = {{You Can Do It: Mitigating RL Rollout Distress with Psychological Guidance}},
  author = {Jack Thompson and Anastasia Wei},
  year = {2026},
  month = aug,
  note = {Submitted to Digital Minds Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/you-can-do-it-mitigating-rl-rollout-distress-with-psychological-guidance-ww7x}},
  url = {https://apartresearch.com/sprints/projects/you-can-do-it-mitigating-rl-rollout-distress-with-psychological-guidance-ww7x}
}

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