We have 3 of 12 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accurate rewards and effective online rollouts. We observe in-domain gains with out-of-domain degradation, exposing two limitations: unreliable spatial rewards in open-world...
Learning Reference Coordinate Frames for Perspective Taking is introduced, a framework that trains VLMs to construct and use explicit reference frames for viewpoint-dependent reasoning and consistently improves over its backbone and achieves strong performance against existing open-source methods.
DG-Mem is proposed, a dual-grained agentic memory framework that augments a frozen MLLM with a non-parametric, externally stored memory built once from training-time rollouts and consulted read-only at test time, and improves consistently over no-memory and competitive memory baselines.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
