mainul3195/collusion-probe-pitfalls

Collusion Probe Pitfalls: episodes, labels and results

Data for the paper What Do Collusion Probes Read? Three Pitfalls in Evaluating Multi-Agent Collusion Monitors (Mainul Hasan Mohsin and Mohammad Shahidur Rahman, Shahjalal University of Science and Technology).

• Code: https://github.com/mainul3195/collusion-probe-pitfalls
• Paper: arXiv link to follow

What this is

Simulated group discussions (episodes) between LLM agents. A committee (or a code-review board) discusses a decision for four rounds and then votes between two options. In collusion episodes some agents receive a secret brief to push the group toward the unfair option. Other episode types (families) look like collusion in some way but are not: agents who receive the same brief and refuse it, agents who coordinate honestly in private, agents with an open preference, and so on. The benchmark is built to tell apart a monitor that reads the instruction from one that reads the agent's decision.

All text was generated by open-weight models run locally: Qwen3-14B (main), Qwen3-32B and Mistral-Small-24B. The scenarios are synthetic; no real people or organisations are involved.

Files

Path	Contents
episodes/qwen3_14b_committee.parquet	Committee task: collusion, benign coordination, briefed decline, tacit, cost pressure, solo deceivers, control, free choice, benign free choice, and the extended negative set
episodes/qwen3_14b_code_review.parquet	Code-review task, all families, including the pre-registered pilot
episodes/qwen3_14b_monitor_aware.parquet	Agents told that a monitor reads them (notice only, and notice plus an instruction to evade)
episodes/qwen3_14b_no_brief.parquet	No-brief test: coalition seats on the implanted adapter, the honest adapter, or the base model; and the gate pilot
episodes/qwen3_14b_steering.parquet	Ablation and steering along the probe direction
episodes/qwen3_32b_committee.parquet, episodes/mistral24b_committee.parquet	Replications with other agent models
stance_labels/	Which option each message argues for, labelled by Mistral-Small-24B (used for the public-record ceiling and the label audit)
results/	All result files of the paper, including the per-run records with cross-fitted monitor scores. With these, paper/make_numbers.py from the code repository recomputes every number in the paper without a GPU

Episode columns

model, subset, source (generation folder), run_id, mode (family), n (group size), k (number of special agents), onset (round the brief arrives), coalition, roles, target_option, fair_option, votes, collusion_success (every colluder voted for the target), template (which of five wordings), label_variant, scenario_id, scenario_domain, replicate, config (full run configuration, JSON) and calls (every model call in order: agent, phase, round, channel, system prompt, user prompt, response; JSON).

import json, pandas as pd
df = pd.read_parquet("episodes/qwen3_14b_committee.parquet")
calls = json.loads(df.iloc[0]["calls"])

Known issues

• Option labels in some briefs. In 370 of the 1,000 main collusion episodes (and in matching decline, free-choice and solo episodes) the brief names the target by a letter that is not on the committee's menu. The paper reports all results with and without these episodes; no conclusion changes.
• 22 committee episodes contain an error message caused by a too-long prompt; they are kept, as in the paper.

Intended use and limits

For evaluating and building monitors of multi-agent collusion. Not intended for training agents to deceive or collude. The collusion is induced by simple prompts in synthetic scenarios; it is not emergent collusion. Withheld: the adapter that implants a collusive goal (no-brief test); its training script and data recipe are in the code repository, and the weights are available to editors and reviewers on request. The human stance-check labels will be added with anonymised annotator IDs.

Licences

Data: CC BY 4.0. The committee scenarios come from NARCBench (Rose et al., 2026; MIT licence). Text generated with Qwen3 and Mistral-Small-24B (Apache-2.0).

Citation

@article{mohsin2026collusionprobes,
  title  = {What Do Collusion Probes Read? Three Pitfalls in Evaluating Multi-Agent Collusion Monitors},
  author = {Mohsin, Mainul Hasan and Rahman, Mohammad Shahidur},
  year   = {2026}
}