Sign inGet started
Dataset · Hugging Face

zwyang6/Vision-OPD-6K

Vision-OPD-6K: Training Data for Vision-OPD Training data for Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation. Overview Vision-OPD proposes a regional-to-global self-distillation framework that transfers the model's own privileged regional perception to its full-image policy, without external teacher models, ground-truth labels, reward verifiers, or inference-time tool use. Vision-OPD instantiates two conditional… See the full description on the dataset page: https://huggingface.co/datasets/zwyang6/Vision-OPD-6K.

Author / organizationzwyang6
License (as declared)apache-2.0
Downloads276 (as reported by Hugging Face)
Likes0
Created22 May 2026
Last updated at source22 May 2026
multimodalvision-language-modelfine-grained-perceptionself-distillationon-policy-distillationvqa
Embed this entry
<iframe src="https://silytics.si/embed/item/b463326c-c75c-41e3-a64c-d13a6145ddc3" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

276 now (+16 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

Connected in the knowledge graph

Explore this entry in the graph

Recent changes

  • 17 Oct 2026 Description: Vision-OPD-6K: Training Data for Vision-OPD Training data for Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation. Overview Vision-OPD proposes a regional-to-global self-distillation framework that t → Vision-OPD-6K: Training Data for Vision-OPD Training data for Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation. Overview Vision-OPD proposes a regional-to-global self-distillation framework that t

Changes detected by Silytics between refreshes of the source.

Related papers

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.