界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
开发与工程 · SKILL.md

pope_recovery_harness

pope_recovery_harness

【开发与工程】Run a bounded POPE proxy recovery experiment with auditable generated-skill invocations and metrics.

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

GitHub

name: pope_recovery_harness description: Run a bounded POPE proxy recovery experiment with auditable generated-skill invocations and metrics.

POPE Recovery Harness

Use this skill during Paper2Skills recovery for the POPE hallucination-evaluation paper when full LVLM evaluation is too expensive or unavailable and soft-mode proxy recovery is allowed. It must be used with the protocol builder, negative sampling, and answer evaluator skills.

Do not use this skill to read the original POPE repository during recovery. It should consume only the paper artifacts, module plan, generated skills, runtime handoff, and current recovery data.

Inputs

  • Attempt directory containing module_plan.json and environment/runtime_handoff.json.
  • Generated skill root containing POPE protocol, sampling, and evaluator skills.
  • Optional tiny annotation records; otherwise the harness creates a mechanism-faithful synthetic dataset.

Outputs

  • recovery/recovery_result.json with metrics and mechanism checks.
  • recovery/logs/generated_data_item.json with records, questions, answers, and per-strategy metrics.
  • recovery/logs/generated_skill_invocations.json proving generated skills were imported and called.
  • recovery/source_manifest.json identifying allowed sources.

Workflow

  1. Read the module plan target and runtime handoff.
  2. Create or load a tiny annotation-style object dataset.
  3. Import and call pope_protocol_builder for random, popular, and adversarial strategies.
  4. Use a deterministic answerer that answers positives correctly and introduces one controlled false positive to exercise hallucination metrics.
  5. Import and call pope_answer_evaluator for every strategy.
  6. Aggregate F1, accuracy, yes ratio, and mechanism checks.
  7. Write all recovery artifacts and leave validation to Distiller's recovery experiment validator.

Validation

Run:

python scripts/run_pope_recovery.py --self-test
python tests/test_recovery_harness.py

A full Distiller attempt should then run recover-paper/scripts/validate_recovery_experiment.py on the attempt directory.

Limitations

This harness is a reduced proxy, not full LVLM inference on COCO. It is acceptable only when soft recovery is configured and the proxy is declared in the recovery plan and result.

我的收藏