6 citations · 9 across the 14 of their papers we have counts for
6 papers · 1 filter
Rewarding Reasoning, Not Answers: Fixing and Bounding Test-Time Reinforcement Learning on Medical QA
Kailong Fan, Anqi Pu, Yichen Wu +7
Test-time reinforcement learning adapts a model on its own unlabeled test set using majority-vote pseudo-labels and has shown strong results in mathematics. We show that this recip…
MAC-Splat: Multi-Attribute Consistency for High-Fidelity Sparse-View Reconstruction
Jinqian Yang, Yichen Wu, Wanhua Li +4
Reconstructing high-fidelity 3D scenes from sparse-views remains a central problem in generalizable neural rendering. Existing generalizable 3D Gaussian Splatting (3DGS) methods of…
DETRAM: End-to-end DEtection, Tracking and Recovery of HumAn Meshes
Chunggi Lee, Seonwook Park, Wanhua Li +2
In the task of human mesh recovery (HMR), multi-person scenes are particularly difficult to handle due to the many entities that appear and occlusions between them over time. In pa…
RiGS: Rigid-aware 4D Gaussian Splatting from a Single Monocular Video
Chenyu Wu, Wanhua Li, Zhu-Tian Chen +1
Reconstructing dynamic 3D scenes from monocular videos is a fundamental yet highly challenging task, as real-world motions often involve both long-term smooth transformations and s…
LangFlash: Feed-forward 3D Language Gaussian Splatting from Sparse Unposed Images
Yilong Liu, Wanhua Li, Chen Zhu-Tian +1
We present LangFlash, a feed-forward framework for 3D Language Gaussian Splatting that reconstructs 3D scenes parameterized by Gaussian primitives enriched with language-aligned se…
MAPLE: Elevating Medical Reasoning from Statistical Consensus to Process-Led Alignment
Kailong Fan, Anqi Pu, Yichen Wu +7
Recent advances in medical large language models have explored Test-Time Reinforcement Learning (TTRL) to enhance reasoning. However, standard TTRL often relies on majority voting…