37 citations · 62 across the 12 of their papers we have counts for
12 papers
From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation
Yibin Liu, Yaxing Lyu, Daqi Gao +5
Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video MLLMs, trained primarily under a Supervi…
Rethinking Intermediate Representation for VLM-based Robot Manipulation
Weiliang Tang, Jialin Gao, Jia-Hui Pan +6
Vision-Language Model (VLM) is an important component to enable robust robot manipulation. Yet, using it to translate human instructions into an action-resolvable intermediate repr…
Mixture of Horizons in Action Chunking
Dong Jing, Gang Wang, Jiaqi Liu +7
Vision-language-action (VLA) models have shown remarkable capabilities in robotic manipulation, but their performance is sensitive to the used during…
COS3D: Collaborative Open-Vocabulary 3D Segmentation
Runsong Zhu, Ka-Hei Hui, Zhengzhe Liu +5
Open-vocabulary 3D segmentation is a fundamental yet challenging task, requiring a mutual understanding of both segmentation and language. However, existing Gaussian-splatting-base…
Incentivizing Multimodal Reasoning in Large Models for Direct Robot Manipulation
Weiliang Tang, Dong Jing, Jia-Hui Pan +5
Recent Large Multimodal Models have demonstrated remarkable reasoning capabilities, especially in solving complex mathematical problems and realizing accurate spatial perception. O…
GeoManip: Geometric Constraints as General Interfaces for Robot Manipulation
Weiliang Tang, Jia-Hui Pan, Yun-Hui Liu +4
We present GeoManip, a framework to enable generalist robots to leverage essential conditions derived from object and part relationships, as geometric constraints, for robot manipu…
Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos
Yi Chen, Yuying Ge, Weiliang Tang +5
Recent developments in Large Language Models pre-trained on extensive corpora have shown significant success in various natural language processing tasks with minimal fine-tuning.…
Embodiment-Agnostic Action Planning via Object-Part Scene Flow
Weiliang Tang, Jia-Hui Pan, Wei Zhan +6
Observing that the key for robotic action planning is to understand the target-object motion when its associated part is manipulated by the end effector, we propose to generate the…
SKU-Patch: Towards Efficient Instance Segmentation for Unseen Objects in Auto-Store
Biqi Yang, Weiliang Tang, Xiaojie Gao +4
In large-scale storehouses, precise instance masks are crucial for robotic bin picking but are challenging to obtain. Existing instance segmentation methods typically rely on a ted…
SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
Wu Zheng, Weiliang Tang, Li Jiang +1
We present Self-Ensembling Single-Stage object Detector (SE-SSD) for accurate and efficient 3D object detection in outdoor point clouds. Our key focus is on exploiting both soft an…
CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud
Wu Zheng, Weiliang Tang, Sijin Chen +2
Existing single-stage detectors for locating objects in point clouds often treat object localization and category classification as separate tasks, so the localization accuracy and…
ReabsNet: Detecting and Revising Adversarial Examples
Jiefeng Chen, Zihang Meng, Changtian Sun +2
Though deep neural network has hit a huge success in recent studies and applica- tions, it still remains vulnerable to adversarial perturbations which are imperceptible to humans.…