# THUDM/ImageReward

- id: src_01M569CRJHDJK3K76M26J4JZ90
- type: source · status: active · revision: 2
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T09, T05, T20 · tags: level:advanced, reward-model, human-preference, text-to-image, scoring, code:python
- updated: 2026-10-18T01:24:43.795Z
- url: https://veyrul.com/sources/src_01M569CRJHDJK3K76M26J4JZ90

Source: https://github.com/zai-org/imagereward

L07 2026-10-17: canonical URL updated from https://github.com/THUDM/ImageReward (GitHub redirect to https://github.com/zai-org/ImageReward). L07 2026-10-17: merged duplicate records from lane-d:zai-org--imagereward (same canonical URL).

```json
{
  "archived": false,
  "checked_at": "2026-10-17T00:00:00.000Z",
  "parent_url": null,
  "usefulness": "Human-preference reward model for text-to-image outputs (NeurIPS 2023) with scoring, ranking and ReFL fine-tuning. Automatic ranking of candidate generations; measures preference/alignment, not identity consistency.",
  "source_type": "repository",
  "availability": "available",
  "dependencies": [],
  "source_owner": null,
  "next_check_at": "2026-10-31T00:00:00.000Z",
  "successor_url": null,
  "hardware_notes": null,
  "known_limitations": [
    "A single scalar preference score; README names a successor (VisionReward) whose page was not fetched.",
    "Preference scores encode annotator taste; domain shift on film/design imagery untested."
  ],
  "upstream_updated_at": "2025-10-29T13:40:51.000Z"
}
```

Evidence claims:
- [upstream_claim] README: first general-purpose text-to-image human-preference reward model, trained on 137k expert comparison pairs, paper arXiv:2304.05977 (NeurIPS 2023); includes ReFL fine-tuning and a Stable Diffusion Web UI scoring script. · source: https://github.com/THUDM/ImageReward
- [upstream_claim] README points to a successor, VisionReward, released 2024/12/31; pip install image-reward then RM.load('ImageReward-v1.0') and model.score(prompt, images). · source: https://github.com/THUDM/ImageReward
- [upstream_claim] README: first general-purpose text-to-image human preference reward model trained on 137k expert comparison pairs, reported to outperform CLIP, Aesthetic and BLIP scoring; ReFL tuning wins 58.4% against untuned Stable Diffusion in human evaluation (upstream claims). · locator: README intro · source: https://github.com/zai-org/ImageReward
- [sourced_fact] Repo now at zai-org/ImageReward (earlier path THUDM/ImageReward returned a redirect via GitHub API); Apache-2.0, not archived, last push 2025-10-29; HF model THUDM/ImageReward tagged apache-2.0. · locator: GitHub API fields; HF API tags · source: https://huggingface.co/api/models/THUDM/ImageReward
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.

Rights:
- code: license=Apache-2.0 hosting=permitted redistribution=permitted modification=permitted training=unknown · Repository page states Apache-2.0. · evidence: https://github.com/THUDM/ImageReward
- dataset: license=unknown hosting=unknown redistribution=unknown modification=unknown training=unknown · ImageRewardDB license not checked. · evidence: https://github.com/THUDM/ImageReward
- model_weights: license=unknown hosting=unknown redistribution=unknown modification=unknown training=unknown · ImageReward-v1.0 model weights license not checked.

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