32 citations · 34 across the 5 of their papers we have counts for
7 papers
PENDULUM: A Benchmark for Assessing Sycophancy in Multimodal Large Language Models
A. B. M. Ashikur Rahman, Saeed Anwar, Muhammad Usman +2
Sycophancy, an excessive tendency of AI models to agree with user input at the expense of factual accuracy or in contradiction of visual evidence, poses a critical and underexplore…
PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation
Yong He, Hongshan Yu, Mingtao Feng +5
Diffusion probabilistic models are traditionally used to generate colors at fixed pixel positions in 2D images. Building on this, we extend diffusion models to point cloud semantic…
Deep learning based infrared small object segmentation: Challenges and future directions
Zhengeng Yang, Hongshan Yu, Jianjun Zhang +2
Infrared sensing is a core method for supporting unmanned systems, such as autonomous vehicles and drones. Recently, infrared sensors have been widely deployed on mobile and statio…
DefAn: Definitive Answer Dataset for LLMs Hallucination Evaluation
A B M Ashikur Rahman, Saeed Anwar, Muhammad Usman +1
Large Language Models (LLMs) have demonstrated remarkable capabilities, revolutionizing the integration of AI in daily life applications. However, they are prone to hallucinations,…
Text-guided 3D Human Motion Generation with Keyframe-based Parallel Skip Transformer
Zichen Geng, Caren Han, Zeeshan Hayder +3
Text-driven human motion generation is an emerging task in animation and humanoid robot design. Existing algorithms directly generate the full sequence which is computationally exp…
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data
Aakash Kumar, Chen Chen, Ajmal Mian +2
3D detection is a critical task that enables machines to identify and locate objects in three-dimensional space. It has a broad range of applications in several fields, including a…
Soft Masked Transformer for Point Cloud Processing with Skip Attention-Based Upsampling
Yong He, Hongshan Yu, Chaoxu Mu +5
Point cloud processing methods leverage local and global point features %at the feature level to cater to downstream tasks, yet they often overlook the task-level context inherent…