2 citations · 4 across the 6 of their papers we have counts for
6 papers
Dynamic Important Example Mining for Reinforcement Finetuning
Haoru Tan, Sitong Wu, Yanfeng Chen +9
Reinforcement fine-tuning (RFT) is increasingly used to strengthen the reasoning abilities of large models, yet its effectiveness is bound by how training data are selected and use…
Dataset Distillation by Influence Matching
Haoru Tan, Wang Wang, Sitong Wu +5
We revisit dataset distillation from an outcome-centric perspective. Rather than aligning process surrogates (per-step gradients or training trajectories), Influence Matching (Inf-…
Object-level Scene Deocclusion
Zhengzhe Liu, Qing Liu, Chirui Chang +6
Deoccluding the hidden portions of objects in a scene is a formidable task, particularly when addressing real-world scenes. In this paper, we present a new self-supervised PArallel…
How Far are AI-generated Videos from Simulating the 3D Visual World: A Learned 3D Evaluation Approach
Chirui Chang, Jiahui Liu, Zhengzhe Liu +6
Recent advancements in video diffusion models enable the generation of photorealistic videos with impressive 3D consistency and temporal coherence. However, the extent to which the…
Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction
Xiaoyang Lyu, Chirui Chang, Peng Dai +2
Scene reconstruction from multi-view images is a fundamental problem in computer vision and graphics. Recent neural implicit surface reconstruction methods have achieved high-quali…
MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds
Jiahui Liu, Chirui Chang, Jianhui Liu +3
3D semantic segmentation on multi-scan large-scale point clouds plays an important role in autonomous systems. Unlike the single-scan-based semantic segmentation task, this task re…