12 citations · 20 across the 13 of their papers we have counts for
13 papers
ExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation
Gaoge Han, Zhengqing Gao, Ziwen Li +5
We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must follow instruction-specified execution co…
PosA-VLA: Enhancing Action Generation via Pose-Conditioned Anchor Attention
Ziwen Li, Xin Wang, Hanlue Zhang +8
The Vision-Language-Action (VLA) models have demonstrated remarkable performance on embodied tasks and shown promising potential for real-world applications. However, current VLAs…
AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection
Yichen Jiang, Mohammed Talha Alam, Sohail Ahmed Khan +2
Detectors of AI-generated images tend to inherit the biases of the data they are trained on: models fitted to GAN imagery learn to treat GAN-specific artifacts as the very definiti…
REMONI: An Autonomous System Integrating Wearables and Multimodal Large Language Models for Enhanced Remote Health Monitoring
Thanh Cong Ho, Farah Kharrat, Abderrazek Abid +1
With the widespread adoption of wearable devices in our daily lives, the demand and appeal for remote patient monitoring have significantly increased. Most research in this field h…
Vision Language Models for Dynamic Human Activity Recognition in Healthcare Settings
Abderrazek Abid, Thanh-Cong Ho, Fakhri Karray
As generative AI continues to evolve, Vision Language Models (VLMs) have emerged as promising tools in various healthcare applications. One area that remains relatively underexplor…
FaceAnonyMixer: Cancelable Faces via Identity Consistent Latent Space Mixing
Mohammed Talha Alam, Fahad Shamshad, Fakhri Karray +1
Advancements in face recognition (FR) technologies have amplified privacy concerns, necessitating methods that protect identity while maintaining recognition utility. Existing face…
FilterLLM: Text-To-Distribution LLM for Billion-Scale Cold-Start Recommendation
Ruochen Liu, Hao Chen, Yuanchen Bei +6
Large Language Model (LLM)-based cold-start recommendation systems continue to face significant computational challenges in billion-scale scenarios, as they follow a "Text-to-Judgm…
UrbanGS: Semantic-Guided Gaussian Splatting for Urban Scene Reconstruction
Ziwen Li, Jiaxin Huang, Runnan Chen +5
Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown st…
Reference-free Hallucination Detection for Large Vision-Language Models
Qing Li, Jiahui Geng, Chenyang Lyu +3
Large vision-language models (LVLMs) have made significant progress in recent years. While LVLMs exhibit excellent ability in language understanding, question answering, and conver…
AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations
Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1
The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion produc…
CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging
Raza Imam, Mohammed Talha Alam, Umaima Rahman +2
Existing vision-text contrastive learning models enhance representation transferability and support zero-shot prediction by matching paired image and caption embeddings while pushi…
FLARE up your data: Diffusion-based Augmentation Method in Astronomical Imaging
Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1
The intersection of Astronomy and AI encounters significant challenges related to issues such as noisy backgrounds, lower resolution (LR), and the intricate process of filtering an…
Large Language Model Simulator for Cold-Start Recommendation
Feiran Huang, Yuanchen Bei, Zhenghang Yang +6
Recommending cold items remains a significant challenge in billion-scale online recommendation systems. While warm items benefit from historical user behaviors, cold items rely sol…