3 citations · 4 across the 28 of their papers we have counts for
13 papers · 1 filter
ACD: Direct Conditional Control for Video Diffusion Models via Attention Supervision
Weiqi Li, Zehao Zhang, Liang Lin +1
Controllability is a fundamental requirement in video synthesis, where accurate alignment with conditioning signals is essential. Existing classifier-free guidance methods typicall…
Human-Centric Open-Future Task Discovery: Formulation, Benchmark, and Scalable Tree-Based Search
Zijian Song, Xiaoxin Lin, Tao Pu +3
Recent progress in robotics and embodied AI is largely driven by Large Multimodal Models (LMMs). However, a key challenge remains underexplored: how can we advance LMMs to discover…
VLA Models Are More Generalizable Than You Think: Revisiting Physical and Spatial Modeling
Weiqi Li, Quande Zhang, Ruifeng Zhai +2
Vision-language-action (VLA) models achieve strong in-distribution performance but degrade sharply under novel camera viewpoints and visual perturbations. We show that this brittle…
In-Situ Tweedie Discrete Diffusion Models
Xiao Li, Jiaqi Zhang, Shuxiang Zhang +3
While diffusion models excel at generating continuous data such as images, adapting them to discrete tasks has relied on indirect approaches that either operate in continuous embed…
E0: Enhancing Generalization and Fine-Grained Control in VLA Models via Tweedie Discrete Diffusion
Zhihao Zhan, Jiaying Zhou, Likui Zhang +10
Vision-Language-Action (VLA) models offer a unified framework for robotic manipulation by integrating visual perception, language understanding, and control generation. However, ex…
UML-CoT: Structured Reasoning and Planning with Unified Modeling Language for Robotic Room Cleaning
Hongyu Chen, Guangrun Wang
Chain-of-Thought (CoT) prompting improves reasoning in large language models (LLMs), but its reliance on unstructured text limits interpretability and executability in embodied tas…
Physical Autoregressive Model for Robotic Manipulation without Action Pretraining
Zijian Song, Sihan Qin, Tianshui Chen +2
The scarcity of manipulation data has motivated the use of pretrained large models from other modalities in robotics. In this work, we build upon autoregressive video generation mo…
GS: Generative Segmentation via Label Diffusion
Yuhao Chen, Shubin Chen, Liang Lin +1
Language-driven image segmentation is a fundamental task in vision-language understanding, requiring models to segment regions of an image corresponding to natural language express…
ReaLM: Reflection-Enhanced Autonomous Reasoning with Small Language Models
Yuanfeng Xu, Zehui Dai, Jian Liang +4
Small Language Models (SLMs) are a cost-effective alternative to Large Language Models (LLMs), but often struggle with complex reasoning due to their limited capacity and a tendenc…
HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics
Weiqi Li, Zehao Zhang, Liang Lin +1
\textbf{Synthetic human dynamics} aims to generate photorealistic videos of human subjects performing expressive, intention-driven motions. However, current approaches face two cor…
One Model for All: Unified Try-On and Try-Off in Any Pose via LLM-Inspired Bidirectional Tweedie Diffusion
Jinxi Liu, Zijian He, Guangrun Wang +2
Recent diffusion-based approaches have made significant advances in image-based virtual try-on, enabling more realistic and end-to-end garment synthesis. However, most existing met…
SIRI-Bench: Challenging VLMs' Spatial Intelligence through Complex Reasoning Tasks
Zijian Song, Xiaoxin Lin, Qiuming Huang +3
Large Language Models (LLMs) have undergone rapid progress, largely attributed to reinforcement learning on complex reasoning tasks. In contrast, while spatial intelligence is fund…
Implicit Neural Representations for Chemical Reaction Paths
Kalyan Ramakrishnan, Lars L. Schaaf, Chen Lin +2
We show that neural networks can be optimized to represent minimum energy paths as continuous functions, offering a flexible alternative to discrete path-search methods such as Nud…