in-context
X2I-in-context-learning
X2I Dataset
Project Page: https://vectorspacelab.github.io/OmniGen/
Github: https://github.com/VectorSpaceLab/OmniGen
Paper: https://arxiv.org/abs/2409.11340
Model: https://huggingface.co/Shitao/OmniGen-v1
To achieve robust multi-task processing capabilities, it is essential to train the OmniGen on large-scale and diverse datasets. However, in the field of unified image generation, a readily available dataset has yet to emerge. For this reason, we have curated a large-scale… See the full description on the dataset page: https://huggingface.co/datasets/yzwang/X2I-in-context-learning.word_in_contextDataset homepage:
https://wic-ita.github.io/index.html
recycling-in-common-contextgpcv_incontext_benchaloha_incontext
aloha_incontext
A Mobile ALOHA robot manipulation dataset for in-context imitation learning. It contains
human-teleoperated demonstrations of pick-and-place, pen uncapping, placing eggs in a
box and closing it, and additional bimanual tasks.
1,328 episodes / 31 task configurations / 587,000 frames, recorded at 50 Hz.
The task configurations are divided into 25 seen configurations (1,318 episodes)
and 6 unseen configurations (10 episodes).
Observations and actions… See the full description on the dataset page: https://huggingface.co/datasets/vo2yager/aloha_incontext.in-context-grid-reasoning
In-Context Grid Reasoning (ICGR)
A small, fully synthetic benchmark for demonstration-conditioned rule induction:
each task shows 2–4 (input grid → output grid) support pairs that share one
hidden transformation, and the model must apply the same transformation to a
held-out query input.
It targets the same behaviour probed by recent in-context / latent-reasoning work
on ARC-AGI (e.g. BDH-CQ: In-Context Learning with Recurrent Latent Reasoning,
arXiv:2608.09888), but is… See the full description on the dataset page: https://huggingface.co/datasets/WhySoCodius/in-context-grid-reasoning.