4 citations · 5 across the 8 of their papers we have counts for
8 papers
Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models
Haoran Hao, Shahram Najam Syed, Jeff Schneider +1
While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performance can degrade when adapted to…
FAR: Failure-Aware Retry for Test-Time Recovery and Continual Policy Improvement
Haoran Hao, Shahram Najam Syed, Jeffrey Ichnowski +1
Robot policies inevitably encounter failures when deployed in real environments. Naive retries often repeat the same mistakes, while many existing recovery methods rely on human in…
Reason Twice: Segmentation via Candidate Discovery and Comparative Reasoning
Xinyan Gao, Haoran Hao, Xiangyu Yue
The rapid development of pretrained foundation models has enabled more general image segmentation. Multimodal large language models (MLLMs) have been widely explored for image segm…
Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation
Shahram Najam Syed, Arthur Jakobsson, Haoran Hao +1
Vision-Language-Action (VLA) models generalize across static manipulation but fail when objects move during task execution. They map the current observation to an action and assume…
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Weiyun Wang, Zhangwei Gao, Lixin Gu +72
We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…
Multimodal Long Video Modeling Based on Temporal Dynamic Context
Haoran Hao, Jiaming Han, Yiyuan Zhang +1
Recent advances in Large Language Models (LLMs) have led to significant breakthroughs in video understanding. However, existing models still struggle with long video processing due…
Learning for Long-Horizon Planning via Neuro-Symbolic Abductive Imitation
Jie-Jing Shao, Hao-Ran Hao, Xiao-Wen Yang +1
Recent learning-to-imitation methods have shown promising results in planning via imitating within the observation-action space. However, their ability in open environments remains…
RAP: Retrieval-Augmented Personalization for Multimodal Large Language Models
Haoran Hao, Jiaming Han, Changsheng Li +2
The development of large language models (LLMs) has significantly enhanced the capabilities of multimodal LLMs (MLLMs) as general assistants. However, lack of user-specific knowled…