UniAR Steering Eval — text quadrants (samples only)
Activation-steering text generations from UniAR (Qwen3-VL backbone, BSQ visual tokens, SD3 decoder).
Raw generated samples only — the LLM-judge scores have been removed.
Quadrants (2, text output)
A steering direction is extracted from minimal pairs in one modality, then injected during pure text generation.
| sub | vector from | steers | output |
|---|---|---|---|
txt2txt |
text pairs | whole user message + generation | text |
img2txt |
image pairs | whole user message + generation | text |
Image-output quadrants (img2img, txt2img) remain under steered-gen/ unchanged.
Sweep
- 7 concepts — semantic:
emotion age cleanness chaos· visual:spatial_lr size near_far - 20 subjects / concept — subject-only, adjectives stripped; the three visual concepts share the same 20 scenes
- prompt:
Describe a/an <subject> as a single frozen snapshot. - 7 layer configs:
L8=[8]L16=[16]L26=[26]early4=[5-8]mid4=[15-18]late4=[26-29]all=[0-35] - alpha:
-0.2 .. 0.2step0.04(10 steered + baseline0.0) - vector:
n100-normalizeddiff-of-means, norm-relative injection; greedy decoding - steer scope: whole user message + every generated token (system prompt, role markers, and special tokens are NOT steered)
Files
steered-gen/{semantic,visual}/<concept>/<quad>/generations.json—{prompts, concept, sub, cells: {"<config>|a<±0.0X>": [20 gens]}, baseline: [20]}(70 cells + baseline)prompts/<concept>/<concept>_text.json— the 20 subject promptsvectors/— steering vectors