SelfReVision

SelfReVision is a lightweight, self-supervised framework for improving vision-language models (VLMs) in procedural planning tasks through iterative self-critique and refinement.

This codebase supports experiments from our paper:

"Making VLMs More Robot-Friendly: Self-Critical Distillation of Low-Level Procedural Reasoning (arXiv 2025)"

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Overview

SelfReVision enables models to iteratively:

• Critique their own outputs
• Revise based on self-generated feedback
• Verify improved versions

We evaluate on image-grounded planning tasks using custom datasets and scripts.

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Code Structure

src/
├── image_filtering.py # Preprocessing utilities for evaluation images
├── inference_only.py # Inference without self-revision
├── llm_judge_eval.py # LLM-as-a-judge evaluation scripts
├── main_blocks.py # Run block-based evaluation
├── main_hamster.py # Run hamster-style evaluation
├── main_selfrevision.py # Main file for SelfReVision: Critique–Revise–Verify
├── main_sft.py # Supervised fine-tuning code after generating training data with SelfReVision

validation-data/
├── block_images/ # Block evaluation images generated with the Ravens simulator
├── hamster_eval_images/ # Hamster task images
├── block_eval.csv # Metadata and instructions for block tasks
├── hamster_eval.csv # Metadata and instructions for hamster tasks
├── vlm_dev_100.csv # Validation set for VLM evaluation (Places data)

Training Data

A larger subset of the Places dataset with GPT-4o-generated plans is available at: https://huggingface.co/datasets/jrfish/SelfReVision

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Citation

If you use this code or dataset, please cite:

@misc{park2025makingvlmsrobotfriendlyselfcritical,
      title={Making VLMs More Robot-Friendly: Self-Critical Distillation of Low-Level Procedural Reasoning}, 
      author={Chan Young Park and Jillian Fisher and Marius Memmel and Dipika Khullar and Andy Yun and Abhishek Gupta and Yejin Choi},
      year={2025},
      eprint={2507.08224},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2507.08224}, 
}