activity
20242026
most citedCurriculum Dataset Distillation

1 citations · 1 across the 22 of their papers we have counts for

collaborators

23 papers

cs.CV2026

Phase-Aligned Finite-Fourier Periodic Deformation for 4D Medical Image Interpolation

Haojin Li, Hengzhuo Wang, Zhiheng Ma +3

4D medical image interpolation aims to recover missing volumes from sparsely observed time points and is important for dynamic anatomical analysis in applications such as cardiac M…

cs.CV2026

Low-Rank Velocity Fields as a Structural Prior for Unsupervised 4D Medical Image Interpolation

Haojin Li, Hengzhuo Wang, Chang Liu +3

Endpoint-only unsupervised 4D medical image interpolation synthesizes intermediate volumes from sparsely sampled sequences with only the start and end volumes available for trainin…

cs.LG2026

DataClaw0: Agentic Tailoring Multimodal Data from Raw Streams

Cong Wan, Zeyu Guo, Zijian Cai +6

Raw multimodal streams are abundant but noisy, redundant, and unaligned with any particular training objective. Turning them into supervision today means either brittle heuristics…

cs.RO2026

DLAM: Distributional Latent Actions with Temporal Constraints

Zuojin Tang, Feifan Luo, Haoyun Liu +10

Vision-language-action (VLA) models remain constrained by scarce action-labeled robot data, whereas action-free videos offer abundant observations of physical change. Latent action…

cs.CV2026

ABot-M0.5: Unified Mobility-and-Manipulation World Action Model

Ronghan Chen, Yandan Yang, Zuojin Tang +18

Mobile manipulation is a key capability for general-purpose robots, yet remains challenging for current embodied learning methods. VLA policies are typically reactive and lack expl…

cs.CV2026

ProSR: Process-Shaped Spatial Reasoning for Reliable Chain-of-Thought in VLMs

Jiangyang Li, Cong Wan, Changjie Wu +8

Reliable spatial reasoning remains a core bottleneck for vision-language models (VLMs). Existing mainstream training paradigms for spatial reasoning largely rely on outcome alignme…