2 citations · 2 across the 9 of their papers we have counts for
11 papers
SIGNPOST-Bench: Benchmarking Text-Vision Conflict Resolution in Multimodal Large Language Models
Sirun Li, Minghao Liu, Ling Dai +4
Multimodal large language models (MLLMs) make grounded predictions in real-world scenes by combining visual and textual cues, yet existing benchmarks rarely reveal how they arbitra…
ForceForget: Reinforcement Concept Removal for Enhancing Safety in Text-to-Image Models
Dong Han, Yong Li
With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, T2I models still can generate unsafe contents. To alleviate…
HDINO: A Concise and Efficient Open-Vocabulary Detector
Hao Zhang, Yiqun Wang, Qinran Lin +2
Despite the growing interest in open-vocabulary object detection in recent years, most existing methods rely heavily on manually curated fine-grained training datasets as well as r…
Securing the Floor and Raising the Ceiling: A Merging-based Paradigm for Multi-modal Search Agents
Zhixiang Wang, Jingxuan Xu, Dajun Chen +3
Recent advances in Vision-Language Models (VLMs) have motivated the development of multi-modal search agents that can actively invoke external search tools and integrate retrieved…
EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent
Jiaao Li, Kaiyuan Li, Chen Gao +2
Egomotion videos are first-person recordings where the view changes continuously due to the agent's movement. As they serve as the primary visual input for embodied AI agents, maki…
AirScape: An Aerial Generative World Model with Motion Controllability
Baining Zhao, Rongze Tang, Mingyuan Jia +9
How to enable agents to predict the outcomes of their own motion intentions in three-dimensional space has been a fundamental problem in embodied intelligence. To explore general s…
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking
Jirong Zha, Yuxuan Fan, Kai Li +4
State estimation is challenging for 3D object tracking with high maneuverability, as the target's state transition function changes rapidly, irregularly, and is unknown to the esti…
Balanced Token Pruning: Accelerating Vision Language Models Beyond Local Optimization
Kaiyuan Li, Xiaoyue Chen, Chen Gao +2
Large Vision-Language Models (LVLMs) have shown impressive performance across multi-modal tasks by encoding images into thousands of tokens. However, the large number of image toke…
PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
Yu Meng, Kaiyuan Li, Chenran Huang +4
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a range of multimodal tasks. However, their inference efficiency is constrained by the large n…
Defining and Evaluating Visual Language Models' Basic Spatial Abilities: A Perspective from Psychometrics
Wenrui Xu, Dalin Lyu, Weihang Wang +3
The Theory of Multiple Intelligences underscores the hierarchical nature of cognitive capabilities. To advance Spatial Artificial Intelligence, we pioneer a psychometric framework…
Understanding and Evaluating Hallucinations in 3D Visual Language Models
Ruiying Peng, Kaiyuan Li, Weichen Zhang +3
Recently, 3D-LLMs, which combine point-cloud encoders with large models, have been proposed to tackle complex tasks in embodied intelligence and scene understanding. In addition to…